Datasets:
pwc-archive
/
links-between-paper-and-code

Dataset card Data Studio Files
xet
Community
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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