Split (1)

train · 300k rows

paper_url stringlengths 36 81	paper_title stringlengths 1 242 ⌀	paper_arxiv_id stringlengths 9 16 ⌀	paper_url_abs stringlengths 18 314	paper_url_pdf stringlengths 21 935 ⌀	repo_url stringlengths 26 200	is_official bool 2 classes	mentioned_in_paper bool 2 classes	mentioned_in_github bool 2 classes	framework stringclasses 9 values
https://paperswithcode.com/paper/spatial-memory-for-context-reasoning-in	Spatial Memory for Context Reasoning in Object Detection	1704.04224	http://arxiv.org/abs/1704.04224v1	http://arxiv.org/pdf/1704.04224v1.pdf	https://github.com/tigerofmurder/tf-faster-rcnn	false	false	true	tf
https://paperswithcode.com/paper/towards-robust-federated-analytics-via	Towards Robust Federated Analytics via Differentially Private Measurements of Statistical Heterogeneity	2411.04579	https://arxiv.org/abs/2411.04579v2	https://arxiv.org/pdf/2411.04579v2.pdf	https://github.com/mary-python/agm-cgm	true	false	false	none
https://paperswithcode.com/paper/facenet-a-unified-embedding-for-face	FaceNet: A Unified Embedding for Face Recognition and Clustering	1503.03832	http://arxiv.org/abs/1503.03832v3	http://arxiv.org/pdf/1503.03832v3.pdf	https://github.com/suyash0612/face_recognitionandverification	false	false	true	tf
https://paperswithcode.com/paper/deep-residual-learning-for-image-recognition	Deep Residual Learning for Image Recognition	1512.03385	http://arxiv.org/abs/1512.03385v1	http://arxiv.org/pdf/1512.03385v1.pdf	https://github.com/Rohed/ml-1	false	false	true	tf
https://paperswithcode.com/paper/you-only-look-once-unified-real-time-object	You Only Look Once: Unified, Real-Time Object Detection	1506.02640	http://arxiv.org/abs/1506.02640v5	http://arxiv.org/pdf/1506.02640v5.pdf	https://github.com/Rohed/ml-1	false	false	true	tf
https://paperswithcode.com/paper/recurrent-attention-model-with-log-polar	Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks	2002.05388	https://arxiv.org/abs/2002.05388v1	https://arxiv.org/pdf/2002.05388v1.pdf	https://github.com/wangxiao5791509/RAM-LPM-PyTorch	false	false	true	pytorch
https://paperswithcode.com/paper/show-and-tell-a-neural-image-caption	Show and Tell: A Neural Image Caption Generator	1411.4555	http://arxiv.org/abs/1411.4555v2	http://arxiv.org/pdf/1411.4555v2.pdf	https://github.com/hashi0203/image-captioning	false	false	true	pytorch
https://paperswithcode.com/paper/mace-model-agnostic-concept-extractor-for	MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks	2011.01472	https://arxiv.org/abs/2011.01472v1	https://arxiv.org/pdf/2011.01472v1.pdf	https://github.com/mace19/MACE	true	true	false	tf
https://paperswithcode.com/paper/meta-learning-for-natural-language	Meta-Learning for Natural Language Understanding under Continual Learning Framework	2011.01452	https://arxiv.org/abs/2011.01452v1	https://arxiv.org/pdf/2011.01452v1.pdf	https://github.com/lexili24/NLUProject	true	true	false	pytorch
https://paperswithcode.com/paper/description-of-quantum-dynamics-of-open	Description of quantum dynamics of open systems based on collision-like models	quant-ph/0410161	https://arxiv.org/abs/quant-ph/0410161v1	https://arxiv.org/pdf/quant-ph/0410161v1.pdf	https://github.com/abhayhegde/qubit-lindblad-form	false	false	true	none
https://paperswithcode.com/paper/effective-distances-for-epidemics-spreading	Effective Distances for Epidemics Spreading on Complex Networks	1608.06201	http://arxiv.org/abs/1608.06201v3	http://arxiv.org/pdf/1608.06201v3.pdf	https://github.com/lucasvt01/Distance_metric_	false	false	true	none
https://paperswithcode.com/paper/global-disease-spread-statistics-and	Global disease spread: statistics and estimation of arrival times	0801.1846	http://arxiv.org/abs/0801.1846v1	http://arxiv.org/pdf/0801.1846v1.pdf	https://github.com/lucasvt01/Distance_metric_	false	false	true	none
https://paperswithcode.com/paper/senteval-an-evaluation-toolkit-for-universal	SentEval: An Evaluation Toolkit for Universal Sentence Representations	1803.05449	http://arxiv.org/abs/1803.05449v1	http://arxiv.org/pdf/1803.05449v1.pdf	https://github.com/HUSTLyn/SentEval	false	false	true	pytorch
https://paperswithcode.com/paper/learning-to-adapt-structured-output-space-for	Learning to Adapt Structured Output Space for Semantic Segmentation	1802.10349	https://arxiv.org/abs/1802.10349v3	https://arxiv.org/pdf/1802.10349v3.pdf	https://github.com/KookHoiKim/AdaptSegNet	false	false	true	pytorch
https://paperswithcode.com/paper/domain-adaptation-for-structured-output-via	Domain Adaptation for Structured Output via Discriminative Patch Representations	1901.05427	https://arxiv.org/abs/1901.05427v4	https://arxiv.org/pdf/1901.05427v4.pdf	https://github.com/KookHoiKim/AdaptSegNet	false	false	true	pytorch
https://paperswithcode.com/paper/adversarial-learning-for-semi-supervised	Adversarial Learning for Semi-Supervised Semantic Segmentation	1802.07934	http://arxiv.org/abs/1802.07934v2	http://arxiv.org/pdf/1802.07934v2.pdf	https://github.com/KookHoiKim/AdaptSegNet	false	false	true	pytorch
https://paperswithcode.com/paper/no-more-discrimination-cross-city-adaptation	No More Discrimination: Cross City Adaptation of Road Scene Segmenters	1704.08509	http://arxiv.org/abs/1704.08509v1	http://arxiv.org/pdf/1704.08509v1.pdf	https://github.com/KookHoiKim/AdaptSegNet	false	false	true	pytorch
https://paperswithcode.com/paper/real-time-hand-gesture-detection-and	Real-time Hand Gesture Detection and Classification Using Convolutional Neural Networks	1901.10323	https://arxiv.org/abs/1901.10323v3	https://arxiv.org/pdf/1901.10323v3.pdf	https://github.com/Blitzkrieg37/Kinesic	false	false	true	tf
https://paperswithcode.com/paper/neural-processes	Neural Processes	1807.01622	http://arxiv.org/abs/1807.01622v1	http://arxiv.org/pdf/1807.01622v1.pdf	https://github.com/wesselb/NeuralProcesses.jl	false	false	true	none
https://paperswithcode.com/paper/yolov4-optimal-speed-and-accuracy-of-object	YOLOv4: Optimal Speed and Accuracy of Object Detection	2004.10934	https://arxiv.org/abs/2004.10934v1	https://arxiv.org/pdf/2004.10934v1.pdf	https://github.com/VinishUchiha/Object-Detection-Using-Yolo4	false	false	true	none
https://paperswithcode.com/paper/improved-evaluation-and-generation-of-grid	Improved Evaluation and Generation of Grid Layouts using Distance Preservation Quality and Linear Assignment Sorting	2205.04255	https://arxiv.org/abs/2205.04255v2	https://arxiv.org/pdf/2205.04255v2.pdf	https://github.com/visual-computing/las_flas	true	true	true	none
https://paperswithcode.com/paper/progressive-growing-of-gans-for-improved	Progressive Growing of GANs for Improved Quality, Stability, and Variation	1710.10196	http://arxiv.org/abs/1710.10196v3	http://arxiv.org/pdf/1710.10196v3.pdf	https://github.com/alexeyhorkin/ProGAN-PyTorch	false	false	true	pytorch
https://paperswithcode.com/paper/reinforcement-learning-with-prototypical	Reinforcement Learning with Prototypical Representations	2102.11271	https://arxiv.org/abs/2102.11271v2	https://arxiv.org/pdf/2102.11271v2.pdf	https://github.com/denisyarats/proto	true	true	true	pytorch
https://paperswithcode.com/paper/the-statistical-mechanics-of-networks	The statistical mechanics of networks	cond-mat/0405566	https://arxiv.org/abs/cond-mat/0405566v1	https://arxiv.org/pdf/cond-mat/0405566v1.pdf	https://github.com/rapharomero/PaperNotes	false	false	true	none
https://paperswithcode.com/paper/a-simple-baseline-for-multi-object-tracking	FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking	2004.01888	https://arxiv.org/abs/2004.01888v6	https://arxiv.org/pdf/2004.01888v6.pdf	https://github.com/ankitsinghsuraj/mot20	false	false	true	pytorch
https://paperswithcode.com/paper/systematically-exploring-redundancy-reduction	Systematically Exploring Redundancy Reduction in Summarizing Long Documents	2012.00052	https://arxiv.org/abs/2012.00052v1	https://arxiv.org/pdf/2012.00052v1.pdf	https://github.com/Wendy-Xiao/redundancy_reduction_longdoc	true	false	false	pytorch
https://paperswithcode.com/paper/a-connectedness-constraint-for-learning	A Connectedness Constraint for Learning Sparse Graphs	1708.09021	http://arxiv.org/abs/1708.09021v1	http://arxiv.org/pdf/1708.09021v1.pdf	https://github.com/MartinSundin/Connected-graph-constraint	false	false	true	none
https://paperswithcode.com/paper/toward-a-generalization-metric-for-deep	Toward a Generalization Metric for Deep Generative Models	2011.00754	https://arxiv.org/abs/2011.00754v3	https://arxiv.org/pdf/2011.00754v3.pdf	https://github.com/htt210/GeneralizationMetricGAN	true	true	false	pytorch
https://paperswithcode.com/paper/uncertainty-guided-continual-learning-with	Uncertainty-guided Continual Learning with Bayesian Neural Networks	1906.02425	https://arxiv.org/abs/1906.02425v2	https://arxiv.org/pdf/1906.02425v2.pdf	https://github.com/SaynaEbrahimi/UCB	true	true	true	pytorch
https://paperswithcode.com/paper/factorised-neural-relational-inference-for	Factorised Neural Relational Inference for Multi-Interaction Systems	1905.08721	https://arxiv.org/abs/1905.08721v1	https://arxiv.org/pdf/1905.08721v1.pdf	https://github.com/quizzicalkudu/shiny-bassoon	false	false	true	pytorch
https://paperswithcode.com/paper/tener-adapting-transformer-encoder-for-name	TENER: Adapting Transformer Encoder for Named Entity Recognition	1911.04474	https://arxiv.org/abs/1911.04474v3	https://arxiv.org/pdf/1911.04474v3.pdf	https://github.com/jaykay233/TF2.0-TENER	false	false	true	tf
https://paperswithcode.com/paper/moviescope-large-scale-analysis-of-movies	Moviescope: Large-scale Analysis of Movies using Multiple Modalities	1908.03180	https://arxiv.org/abs/1908.03180v1	https://arxiv.org/pdf/1908.03180v1.pdf	https://github.com/IsaacRodgz/multimodal-transformers-movies	false	false	true	pytorch
https://paperswithcode.com/paper/quo-vadis-action-recognition-a-new-model-and	Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset	1705.07750	http://arxiv.org/abs/1705.07750v3	http://arxiv.org/pdf/1705.07750v3.pdf	https://github.com/helloxy96/CS5242_Project2020	false	false	true	pytorch
https://paperswithcode.com/paper/h-0-tension-phantom-dark-energy-and	$H_0$ Tension, Phantom Dark Energy and Cosmological Parameter Degeneracies	2004.08363	https://arxiv.org/abs/2004.08363v3	https://arxiv.org/pdf/2004.08363v3.pdf	https://github.com/GeorgeAlestas/H0_Tension_Data	true	true	true	none
https://paperswithcode.com/paper/deformable-linear-object-prediction-using	Deformable Linear Object Prediction Using Locally Linear Latent Dynamics	2103.14184	https://arxiv.org/abs/2103.14184v1	https://arxiv.org/pdf/2103.14184v1.pdf	https://github.com/zwbgood6/deform	true	true	true	pytorch
https://paperswithcode.com/paper/doing-more-by-doing-less-how-structured	Doing More by Doing Less: How Structured Partial Backpropagation Improves Deep Learning Clusters	2111.10672	https://arxiv.org/abs/2111.10672v1	https://arxiv.org/pdf/2111.10672v1.pdf	https://github.com/adarsh-kr/paper_jigsaw-	true	true	false	none
https://paperswithcode.com/paper/a-partially-reversible-u-net-for-memory	A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation	1906.06148	https://arxiv.org/abs/1906.06148v2	https://arxiv.org/pdf/1906.06148v2.pdf	https://github.com/gigantenbein/UNet-Zoo	false	false	true	pytorch
https://paperswithcode.com/paper/a-scripted-control-system-for-autonomous	A scripted control system for autonomous hardware timed experiments	1303.0080	https://arxiv.org/abs/1303.0080v3	https://arxiv.org/pdf/1303.0080v3.pdf	https://github.com/labscript-suite-temp-2-archive/cbillington-installer--forked-from--labscript_suite-installer	false	false	true	none
https://paperswithcode.com/paper/u-net-convolutional-networks-for-biomedical	U-Net: Convolutional Networks for Biomedical Image Segmentation	1505.04597	http://arxiv.org/abs/1505.04597v1	http://arxiv.org/pdf/1505.04597v1.pdf	https://github.com/JifeiWang-WHU/Pytorch_Building_extraction	false	false	true	pytorch
https://paperswithcode.com/paper/road-extraction-by-deep-residual-u-net	Road Extraction by Deep Residual U-Net	1711.10684	http://arxiv.org/abs/1711.10684v1	http://arxiv.org/pdf/1711.10684v1.pdf	https://github.com/JifeiWang-WHU/Pytorch_Building_extraction	false	false	true	pytorch
https://paperswithcode.com/paper/u-net-convolutional-networks-for-biomedical	U-Net: Convolutional Networks for Biomedical Image Segmentation	1505.04597	http://arxiv.org/abs/1505.04597v1	http://arxiv.org/pdf/1505.04597v1.pdf	https://github.com/SharadGitHub/OctaveUnet	false	false	true	pytorch
https://paperswithcode.com/paper/configuration-of-the-atlas-trigger-system	Configuration of the ATLAS Trigger System	physics/0306046	https://arxiv.org/abs/physics/0306046v1	https://arxiv.org/pdf/physics/0306046v1.pdf	https://github.com/mirguest/paper	false	false	true	none
https://paperswithcode.com/paper/phiseg-capturing-uncertainty-in-medical-image	PHiSeg: Capturing Uncertainty in Medical Image Segmentation	1906.04045	https://arxiv.org/abs/1906.04045v2	https://arxiv.org/pdf/1906.04045v2.pdf	https://github.com/gigantenbein/UNet-Zoo	false	false	true	pytorch
https://paperswithcode.com/paper/fully-trainable-deep-matching	Fully-Trainable Deep Matching	1609.03532	http://arxiv.org/abs/1609.03532v1	http://arxiv.org/pdf/1609.03532v1.pdf	https://github.com/vwegn/dm	false	false	true	tf
https://paperswithcode.com/paper/deepmatching-hierarchical-deformable-dense	DeepMatching: Hierarchical Deformable Dense Matching	1506.07656	http://arxiv.org/abs/1506.07656v2	http://arxiv.org/pdf/1506.07656v2.pdf	https://github.com/vwegn/dm	false	false	true	tf
https://paperswithcode.com/paper/the-simple-essence-of-automatic	The simple essence of automatic differentiation	1804.00746	http://arxiv.org/abs/1804.00746v2	http://arxiv.org/pdf/1804.00746v2.pdf	https://github.com/bond15/Haskell-Examples	false	false	true	none
https://paperswithcode.com/paper/a-diagrammatic-axiomatisation-for-qubit	A Diagrammatic Axiomatisation for Qubit Entanglement	1501.07082	https://arxiv.org/abs/1501.07082v1	https://arxiv.org/pdf/1501.07082v1.pdf	https://github.com/bond15/Haskell-Examples	false	false	true	none
https://paperswithcode.com/paper/mixup-beyond-empirical-risk-minimization	mixup: Beyond Empirical Risk Minimization	1710.09412	http://arxiv.org/abs/1710.09412v2	http://arxiv.org/pdf/1710.09412v2.pdf	https://github.com/Yangget/Mixup_All-use	false	false	true	none
https://paperswithcode.com/paper/improving-attacks-on-round-reduced-speck32-64	Improving Attacks on Round-Reduced Speck32/64 Using Deep Learning	null	https://eprint.iacr.org/2019/037.pdf	https://eprint.iacr.org/2019/037.pdf	https://github.com/agohr/deep_speck	false	true	false	tf
https://paperswithcode.com/paper/revisiting-the-inverted-indices-for-billion	Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors	1802.02422	http://arxiv.org/abs/1802.02422v2	http://arxiv.org/pdf/1802.02422v2.pdf	https://github.com/merria28/hnswlib	false	false	true	mxnet
https://paperswithcode.com/paper/solving-statistical-mechanics-using	Solving Statistical Mechanics Using Variational Autoregressive Networks	1809.10606	http://arxiv.org/abs/1809.10606v2	http://arxiv.org/pdf/1809.10606v2.pdf	https://github.com/wangleiphy/VAN.jl	true	false	true	pytorch
https://paperswithcode.com/paper/efficient-and-robust-approximate-nearest	Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs	1603.09320	http://arxiv.org/abs/1603.09320v4	http://arxiv.org/pdf/1603.09320v4.pdf	https://github.com/merria28/hnswlib	false	false	true	mxnet
https://paperswithcode.com/paper/adversarially-guided-actor-critic-1	Adversarially Guided Actor-Critic	2102.04376	https://arxiv.org/abs/2102.04376v1	https://arxiv.org/pdf/2102.04376v1.pdf	https://github.com/yfletberliac/adversarially-guided-actor-critic	true	true	false	tf
https://paperswithcode.com/paper/dynamic-routing-between-capsules	Dynamic Routing Between Capsules	1710.09829	http://arxiv.org/abs/1710.09829v2	http://arxiv.org/pdf/1710.09829v2.pdf	https://github.com/sahil02235/CAPSULE-NETWORK-IMPLEMENTATION	false	false	true	tf
https://paperswithcode.com/paper/perceptual-losses-for-real-time-style	Perceptual Losses for Real-Time Style Transfer and Super-Resolution	1603.08155	http://arxiv.org/abs/1603.08155v1	http://arxiv.org/pdf/1603.08155v1.pdf	https://github.com/anjalipemmaraju/styletransfernetwork	false	false	true	pytorch
https://paperswithcode.com/paper/graph-embedding-on-biomedical-networks	Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations	1906.05017	https://arxiv.org/abs/1906.05017v3	https://arxiv.org/pdf/1906.05017v3.pdf	https://github.com/QustKcz/BioNEV	false	false	true	none
https://paperswithcode.com/paper/time-complexity-analysis-of-an-evolutionary	Time Complexity Analysis of an Evolutionary Algorithm for approximating Nash Equilibriums	2110.13563	https://arxiv.org/abs/2110.13563v1	https://arxiv.org/pdf/2110.13563v1.pdf	https://github.com/AadeshSalecha/evol-sim	true	false	false	none
https://paperswithcode.com/paper/optimal-transport-based-distributionally	Optimal Transport Based Distributionally Robust Optimization: Structural Properties and Iterative Schemes	1810.02403	https://arxiv.org/abs/1810.02403v3	https://arxiv.org/pdf/1810.02403v3.pdf	https://github.com/AndyZhang92/DRO-Portfolio-Opt	false	false	true	none
https://paperswithcode.com/paper/estimation-of-singly-transiting-k2-planet	Estimation of singly-transiting K2 planet periods with Gaia parallaxes	1908.08548	https://arxiv.org/abs/1908.08548v1	https://arxiv.org/pdf/1908.08548v1.pdf	https://github.com/nespinoza/single	true	true	true	none
https://paperswithcode.com/paper/yolov3-an-incremental-improvement	YOLOv3: An Incremental Improvement	1804.02767	http://arxiv.org/abs/1804.02767v1	http://arxiv.org/pdf/1804.02767v1.pdf	https://github.com/jianmingwuhasco/yolov3	false	false	true	pytorch
https://paperswithcode.com/paper/rlpyt-a-research-code-base-for-deep	rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch	1909.01500	https://arxiv.org/abs/1909.01500v2	https://arxiv.org/pdf/1909.01500v2.pdf	https://github.com/akterskii/rlpyt	false	false	true	pytorch
https://paperswithcode.com/paper/accelerated-methods-for-deep-reinforcement	Accelerated Methods for Deep Reinforcement Learning	1803.02811	http://arxiv.org/abs/1803.02811v2	http://arxiv.org/pdf/1803.02811v2.pdf	https://github.com/akterskii/rlpyt	false	false	true	pytorch
https://paperswithcode.com/paper/an-empirical-model-of-large-batch-training	An Empirical Model of Large-Batch Training	1812.06162	http://arxiv.org/abs/1812.06162v1	http://arxiv.org/pdf/1812.06162v1.pdf	https://github.com/akterskii/rlpyt	false	false	true	pytorch
https://paperswithcode.com/paper/sparse-estimation-for-case-control-studies	Sparse estimation for case-control studies with multiple subtypes of cases	1901.01583	https://arxiv.org/abs/1901.01583v2	https://arxiv.org/pdf/1901.01583v2.pdf	https://github.com/NadimBLT/SL1CLR	false	false	true	none
https://paperswithcode.com/paper/gridless-variational-bayesian-channel	Gridless Variational Bayesian Channel Estimation for Antenna Array Systems with Low Resolution ADCs	1906.00576	https://arxiv.org/abs/1906.00576v1	https://arxiv.org/pdf/1906.00576v1.pdf	https://github.com/RiverZhu/GL-QVBCE	false	false	true	none
https://paperswithcode.com/paper/relational-inductive-biases-deep-learning-and	Relational inductive biases, deep learning, and graph networks	1806.01261	http://arxiv.org/abs/1806.01261v3	http://arxiv.org/pdf/1806.01261v3.pdf	https://github.com/DeepaliVerma/https-github.com-deepmind-graph_nets	false	false	true	tf
https://paperswithcode.com/paper/teaching-algebraic-curves-for-gifted-learners	Teaching algebraic curves for gifted learners at age 11 by using LEGO linkages and GeoGebra	1909.04964	https://arxiv.org/abs/1909.04964v3	https://arxiv.org/pdf/1909.04964v3.pdf	https://github.com/kovzol/lego-linkages	true	true	true	none
https://paperswithcode.com/paper/stack-pointer-networks-for-dependency-parsing	Stack-Pointer Networks for Dependency Parsing	1805.01087	http://arxiv.org/abs/1805.01087v1	http://arxiv.org/pdf/1805.01087v1.pdf	https://github.com/XuezheMax/NeuroNLP2	true	true	true	pytorch
https://paperswithcode.com/paper/unsupervised-domain-adaptation-by	Unsupervised Domain Adaptation by Backpropagation	1409.7495	http://arxiv.org/abs/1409.7495v2	http://arxiv.org/pdf/1409.7495v2.pdf	https://github.com/sroutray/da-ganin	false	false	true	pytorch
https://paperswithcode.com/paper/using-deep-learning-for-image-based-plant	Using Deep Learning for Image-Based Plant Disease Detection	1604.03169	http://arxiv.org/abs/1604.03169v2	http://arxiv.org/pdf/1604.03169v2.pdf	https://github.com/abhimangalms/PlantDoctor	false	false	true	tf
https://paperswithcode.com/paper/image-super-resolution-using-deep	Image Super-Resolution Using Deep Convolutional Networks	1501.00092	http://arxiv.org/abs/1501.00092v3	http://arxiv.org/pdf/1501.00092v3.pdf	https://github.com/Weifeng73/Zero-Shot-Super-resolution	false	false	true	none
https://paperswithcode.com/paper/unsupervised-representation-learning-with-1	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks	1511.06434	http://arxiv.org/abs/1511.06434v2	http://arxiv.org/pdf/1511.06434v2.pdf	https://github.com/iamkucuk/DCGAN-Face-Generation	false	false	true	pytorch
https://paperswithcode.com/paper/hyper-process-model-a-zero-shot-learning	Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape Analysis	1810.10330	http://arxiv.org/abs/1810.10330v1	http://arxiv.org/pdf/1810.10330v1.pdf	https://github.com/joaoreis-feup/hyper_process_model	false	false	true	none
https://paperswithcode.com/paper/bert-pre-training-of-deep-bidirectional	BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	1810.04805	https://arxiv.org/abs/1810.04805v2	https://arxiv.org/pdf/1810.04805v2.pdf	https://github.com/liuqiangict/lamb_optimizer	false	false	true	tf
https://paperswithcode.com/paper/the-omniglot-challenge-a-3-year-progress	The Omniglot challenge: a 3-year progress report	1902.03477	https://arxiv.org/abs/1902.03477v2	https://arxiv.org/pdf/1902.03477v2.pdf	https://github.com/farhanhubble/omniglot	false	false	true	none
https://paperswithcode.com/paper/efficientnet-rethinking-model-scaling-for	EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks	1905.11946	https://arxiv.org/abs/1905.11946v5	https://arxiv.org/pdf/1905.11946v5.pdf	https://github.com/filipmu/Kaggle-APTOS-2019-Blindness	false	false	true	pytorch
https://paperswithcode.com/paper/learning-texture-manifolds-with-the-periodic	Learning Texture Manifolds with the Periodic Spatial GAN	1705.06566	http://arxiv.org/abs/1705.06566v2	http://arxiv.org/pdf/1705.06566v2.pdf	https://github.com/oist/psgan	false	false	true	pytorch
https://paperswithcode.com/paper/copy-the-old-or-paint-anew-an-adversarial	Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Image Stylization	1811.09236	http://arxiv.org/abs/1811.09236v1	http://arxiv.org/pdf/1811.09236v1.pdf	https://github.com/oist/psgan	false	false	true	pytorch
https://paperswithcode.com/paper/very-deep-convolutional-networks-for-large	Very Deep Convolutional Networks for Large-Scale Image Recognition	1409.1556	http://arxiv.org/abs/1409.1556v6	http://arxiv.org/pdf/1409.1556v6.pdf	https://github.com/vwegn/dm	false	false	true	tf
https://paperswithcode.com/paper/joint-energy-based-model-training-for-better	Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models	2101.06829	https://arxiv.org/abs/2101.06829v2	https://arxiv.org/pdf/2101.06829v2.pdf	https://github.com/salesforce/ebm_calibration_nlu	true	true	true	pytorch
https://paperswithcode.com/paper/adversarial-parametric-pose-prior	Adversarial Parametric Pose Prior	2112.04203	https://arxiv.org/abs/2112.04203v1	https://arxiv.org/pdf/2112.04203v1.pdf	https://github.com/cvlab-epfl/adv_param_pose_prior	true	false	true	pytorch
https://paperswithcode.com/paper/top-down-neural-attention-by-excitation	Top-down Neural Attention by Excitation Backprop	1608.00507	http://arxiv.org/abs/1608.00507v1	http://arxiv.org/pdf/1608.00507v1.pdf	https://github.com/greydanus/excitationbp	false	false	true	pytorch
https://paperswithcode.com/paper/contrastive-embedding-distribution-refinement	Contrastive Embedding Distribution Refinement and Entropy-Aware Attention for 3D Point Cloud Classification	2201.11388	https://arxiv.org/abs/2201.11388v1	https://arxiv.org/pdf/2201.11388v1.pdf	https://github.com/yangfengseu/cedr	true	true	false	pytorch
https://paperswithcode.com/paper/w2s-a-joint-denoising-and-super-resolution	W2S: Microscopy Data with Joint Denoising and Super-Resolution for Widefield to SIM Mapping	2003.05961	https://arxiv.org/abs/2003.05961v2	https://arxiv.org/pdf/2003.05961v2.pdf	https://github.com/IVRL/w2s	true	true	true	tf
https://paperswithcode.com/paper/maniqa-multi-dimension-attention-network-for	MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment	2204.08958	https://arxiv.org/abs/2204.08958v2	https://arxiv.org/pdf/2204.08958v2.pdf	https://github.com/tianhewu/assessor360	false	false	true	pytorch
https://paperswithcode.com/paper/efficient-one-pass-end-to-end-entity-linking	Efficient One-Pass End-to-End Entity Linking for Questions	2010.02413	https://arxiv.org/abs/2010.02413v1	https://arxiv.org/pdf/2010.02413v1.pdf	https://github.com/shmsw25/GraphRetriever	false	false	true	pytorch
https://paperswithcode.com/paper/kiu-net-towards-accurate-segmentation-of	KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations	2006.04878	https://arxiv.org/abs/2006.04878v2	https://arxiv.org/pdf/2006.04878v2.pdf	https://github.com/jeya-maria-jose/KiU-Net-pytorch	true	true	true	pytorch
https://paperswithcode.com/paper/wide-residual-networks	Wide Residual Networks	1605.07146	http://arxiv.org/abs/1605.07146v4	http://arxiv.org/pdf/1605.07146v4.pdf	https://github.com/georgeretsi/SparsityLoss	false	false	true	pytorch
https://paperswithcode.com/paper/a-theoretically-grounded-application-of	A Theoretically Grounded Application of Dropout in Recurrent Neural Networks	1512.05287	http://arxiv.org/abs/1512.05287v5	http://arxiv.org/pdf/1512.05287v5.pdf	https://github.com/SuperKam91/bnn	false	false	true	tf
https://paperswithcode.com/paper/invertible-generative-modeling-using-linear	Invertible Generative Modeling using Linear Rational Splines	2001.05168	https://arxiv.org/abs/2001.05168v4	https://arxiv.org/pdf/2001.05168v4.pdf	https://github.com/hmdolatabadi/LRS_NF	true	true	true	pytorch
https://paperswithcode.com/paper/image-to-image-translation-with-conditional	Image-to-Image Translation with Conditional Adversarial Networks	1611.07004	http://arxiv.org/abs/1611.07004v3	http://arxiv.org/pdf/1611.07004v3.pdf	https://github.com/tianhai123/pix2pix	false	false	true	torch
https://paperswithcode.com/paper/automatically-optimized-gradient-boosting	Automatically Optimized Gradient Boosting Trees for Classifying Large Volume High Cardinality Data Streams Under Concept Drift	null	https://link.springer.com/chapter/10.1007/978-3-030-29135-8_13	https://link.springer.com/chapter/10.1007/978-3-030-29135-8_13	https://github.com/flytxtds/AutoGBT	false	false	false	none
https://paperswithcode.com/paper/learning-to-orient-surfaces-by-self	Learning to Orient Surfaces by Self-supervised Spherical CNNs	2011.03298	https://arxiv.org/abs/2011.03298v2	https://arxiv.org/pdf/2011.03298v2.pdf	https://github.com/CVLAB-Unibo/compass	true	true	true	pytorch
https://paperswithcode.com/paper/roft-a-tool-for-evaluating-human-detection-of	RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text	2010.03070	https://arxiv.org/abs/2010.03070v1	https://arxiv.org/pdf/2010.03070v1.pdf	https://github.com/kirubarajan/roft	true	true	true	none
https://paperswithcode.com/paper/knowledge-association-with-hyperbolic	Knowledge Association with Hyperbolic Knowledge Graph Embeddings	2010.02162	https://arxiv.org/abs/2010.02162v1	https://arxiv.org/pdf/2010.02162v1.pdf	https://github.com/nju-websoft/HyperKA	true	true	true	tf
https://paperswithcode.com/paper/waveq-gradient-based-deep-quantization-of	WAVEQ: GRADIENT-BASED DEEP QUANTIZATION OF NEURAL NETWORKS THROUGH SINUSOIDAL REGULARIZATION	null	https://openreview.net/forum?id=uELnyih9gqb	https://openreview.net/pdf?id=uELnyih9gqb	https://github.com/waveq-reg/waveq	true	true	false	pytorch
https://paperswithcode.com/paper/attention-forcing-for-machine-translation	Attention Forcing for Machine Translation	2104.01264	https://arxiv.org/abs/2104.01264v1	https://arxiv.org/pdf/2104.01264v1.pdf	https://github.com/3dmaisons/af-mnt	true	true	false	pytorch
https://paperswithcode.com/paper/learning-by-minimizing-the-sum-of-ranked	Learning by Minimizing the Sum of Ranked Range	2010.01741	https://arxiv.org/abs/2010.01741v1	https://arxiv.org/pdf/2010.01741v1.pdf	https://github.com/discovershu/SoRR	true	true	false	pytorch
https://paperswithcode.com/paper/gradient-waveform-design-for-tensor-valued	Gradient waveform design for tensor-valued encoding in diffusion MRI	2007.07631	https://arxiv.org/abs/2007.07631v1	https://arxiv.org/pdf/2007.07631v1.pdf	https://github.com/filip-szczepankiewicz/safe_pns_prediction	true	true	false	none
https://paperswithcode.com/paper/domain-adversarial-fine-tuning-as-an	Domain Adversarial Fine-Tuning as an Effective Regularizer	2009.13366	https://arxiv.org/abs/2009.13366v2	https://arxiv.org/pdf/2009.13366v2.pdf	https://github.com/GeorgeVern/AFTERV1.0	true	true	true	pytorch

Subsets and Splits

Framework Repo Connectivity Analysis

Reveals the number of official and unofficial repositories and papers associated with different frameworks, highlighting the most connected ones.

Deduplicated Paper-Code Links

This query provides a detailed and organized list of repositories linked to single papers, highlighting official status and mention sources, which is useful for understanding the relationship between papers and their corresponding repositories.

Paper Repo Counts & Distribution

Provides detailed statistics on the distribution of papers across different numbers of repositories, highlighting the percentage of papers with multiple repositories.

Quantum Papers with Code Links

Lists quantum-related papers with their titles, arXiv IDs, frameworks, and code repository links, providing a valuable resource for researchers interested in quantum computing.

Financial Stock Price Prediction

Finds papers related to stock prices, financial markets, and predictions, providing a focused subset for further analysis.

SQL Console for pwc-archive/links-between-paper-and-code

Retrieves specific details about a single paper by its arXiv ID, providing limited insight into the dataset.

Search for YOLO Links

Retrieves a limited set of records related to YOLO, providing basic information about papers and repositories but without deeper analysis.

Prompt Optimization and Personalization

Retrieves a limited set of papers with titles containing specific keywords related to prompt optimization and personalization, providing basic filtering of the dataset.