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

Dataset card Data Studio Files
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https://paperswithcode.com/paper/dynotears-structure-learning-from-time-series
DYNOTEARS: Structure Learning from Time-Series Data
2002.00498
https://arxiv.org/abs/2002.00498v2
https://arxiv.org/pdf/2002.00498v2.pdf
https://github.com/lcastri/causalflow
false
false
true
pytorch
https://paperswithcode.com/paper/benchmarking-object-detectors-under-real-1
Benchmarking Object Detectors under Real-World Distribution Shifts in Satellite Imagery
2503.19202
https://arxiv.org/abs/2503.19202v1
https://arxiv.org/pdf/2503.19202v1.pdf
https://github.com/rwgai/rwds
true
true
true
pytorch
https://paperswithcode.com/paper/caraserve-cpu-assisted-and-rank-aware-lora
CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference
2401.11240
https://arxiv.org/abs/2401.11240v1
https://arxiv.org/pdf/2401.11240v1.pdf
https://github.com/modeltc/lightllm
true
true
true
pytorch
https://paperswithcode.com/paper/fastswitch-optimizing-context-switching
FastSwitch: Optimizing Context Switching Efficiency in Fairness-aware Large Language Model Serving
2411.18424
https://arxiv.org/abs/2411.18424v1
https://arxiv.org/pdf/2411.18424v1.pdf
https://github.com/modeltc/lightllm
false
false
true
pytorch
https://paperswithcode.com/paper/amago-2-breaking-the-multi-task-barrier-in
AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers
2411.11188
https://arxiv.org/abs/2411.11188v1
https://arxiv.org/pdf/2411.11188v1.pdf
https://github.com/ut-austin-rpl/amago
true
false
true
pytorch
https://paperswithcode.com/paper/imgedit-a-unified-image-editing-dataset-and
ImgEdit: A Unified Image Editing Dataset and Benchmark
2505.20275
https://arxiv.org/abs/2505.20275v1
https://arxiv.org/pdf/2505.20275v1.pdf
https://github.com/pku-yuangroup/imgedit
true
true
true
pytorch
https://paperswithcode.com/paper/moe-mlora-for-multi-domain-ctr-prediction
MoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert Specialization
2506.07563
https://arxiv.org/abs/2506.07563v3
https://arxiv.org/pdf/2506.07563v3.pdf
https://github.com/Kenyaggel/MLoRA
true
true
false
tf
https://paperswithcode.com/paper/vidore-benchmark-v2-raising-the-bar-for
ViDoRe Benchmark V2: Raising the Bar for Visual Retrieval
2505.17166
https://arxiv.org/abs/2505.17166v1
https://arxiv.org/pdf/2505.17166v1.pdf
https://github.com/illuin-tech/colpali
false
false
true
pytorch
https://paperswithcode.com/paper/multi-task-visual-grounding-with-coarse-to
Multi-task Visual Grounding with Coarse-to-Fine Consistency Constraints
2501.06710
https://arxiv.org/abs/2501.06710v1
https://arxiv.org/pdf/2501.06710v1.pdf
https://github.com/dmmm1997/c3vg
true
true
true
pytorch
https://paperswithcode.com/paper/logicpuzzlerl-cultivating-robust-mathematical
LogicPuzzleRL: Cultivating Robust Mathematical Reasoning in LLMs via Reinforcement Learning
2506.04821
https://arxiv.org/abs/2506.04821v1
https://arxiv.org/pdf/2506.04821v1.pdf
https://github.com/wongzhenhao/GameRL
true
true
false
pytorch
https://paperswithcode.com/paper/craft-customizing-llms-by-creating-and
CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets
2309.17428
https://arxiv.org/abs/2309.17428v2
https://arxiv.org/pdf/2309.17428v2.pdf
https://github.com/charlesq9/alita
false
false
true
none
https://paperswithcode.com/paper/on-path-to-multimodal-historical-reasoning
On Path to Multimodal Historical Reasoning: HistBench and HistAgent
2505.20246
https://arxiv.org/abs/2505.20246v1
https://arxiv.org/pdf/2505.20246v1.pdf
https://github.com/charlesq9/alita
false
false
true
none
https://paperswithcode.com/paper/interpretability-in-the-wild-a-circuit-for
Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small
2211.00593
https://arxiv.org/abs/2211.00593v1
https://arxiv.org/pdf/2211.00593v1.pdf
https://github.com/technion-cs-nlp/peap
false
false
true
jax
https://paperswithcode.com/paper/delving-into-multilingual-ethical-bias-the
Delving into Multilingual Ethical Bias: The MSQAD with Statistical Hypothesis Tests for Large Language Models
2505.19121
https://arxiv.org/abs/2505.19121v1
https://arxiv.org/pdf/2505.19121v1.pdf
https://github.com/seungukyu/msqad
true
true
true
none
https://paperswithcode.com/paper/heterogeneous-networks-in-drug-target
Heterogeneous networks in drug-target interaction prediction
2504.16152
https://arxiv.org/abs/2504.16152v2
https://arxiv.org/pdf/2504.16152v2.pdf
https://github.com/macrohongz/hampdti
true
true
false
pytorch
https://paperswithcode.com/paper/timemaster-training-time-series-multimodal
TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learning
2506.13705
https://arxiv.org/abs/2506.13705v1
https://arxiv.org/pdf/2506.13705v1.pdf
https://github.com/langfengq/timemaster
true
true
true
pytorch
https://paperswithcode.com/paper/speak-easy-eliciting-harmful-jailbreaks-from
Speak Easy: Eliciting Harmful Jailbreaks from LLMs with Simple Interactions
2502.04322
https://arxiv.org/abs/2502.04322v2
https://arxiv.org/pdf/2502.04322v2.pdf
https://github.com/yiksiu-chan/SpeakEasy
true
false
true
pytorch
https://paperswithcode.com/paper/general-complex-polynomial-root-solver-and
General Complex Polynomial Root Solver and Its Further Optimization for Binary Microlenses
1203.1034
http://arxiv.org/abs/1203.1034v1
http://arxiv.org/pdf/1203.1034v1.pdf
https://github.com/giordano/PolynomialRoots.jl
false
false
true
none
https://paperswithcode.com/paper/simulations-and-experiments-with-assemblies
Simulations and experiments with assemblies of fiber-reinforced soft actuators
2507.10121
https://arxiv.org/abs/2507.10121v1
https://arxiv.org/pdf/2507.10121v1.pdf
https://github.com/GazzolaLab/PyElastica
false
false
true
none
https://paperswithcode.com/paper/a-physics-informed-vision-based-method-to
A physics-informed, vision-based method to reconstruct all deformation modes in slender bodies
2109.08372
https://arxiv.org/abs/2109.08372v1
https://arxiv.org/pdf/2109.08372v1.pdf
https://github.com/GazzolaLab/PyElastica
false
false
true
none
https://paperswithcode.com/paper/generalizing-person-re-identification-by
Generalizing Person Re-Identification by Camera-Aware Invariance Learning and Cross-Domain Mixup
null
https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/2329_ECCV_2020_paper.php
https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123600222.pdf
https://github.com/LuckyDC/generalizing-reid
true
true
false
pytorch
https://paperswithcode.com/paper/a-portable-implementation-of-ranlux
A Portable Implementation of RANLUX++
2106.02504
https://arxiv.org/abs/2106.02504v1
https://arxiv.org/pdf/2106.02504v1.pdf
https://github.com/hahnjo/ranluxpp
false
false
true
none
https://paperswithcode.com/paper/scrabblegan-semi-supervised-varying-length
ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation
2003.10557
https://arxiv.org/abs/2003.10557v1
https://arxiv.org/pdf/2003.10557v1.pdf
https://github.com/arshjot/ScrabbleGAN
false
false
true
pytorch
https://paperswithcode.com/paper/mri-super-resolution-using-multi-channel
MRI Super-Resolution using Multi-Channel Total Variation
1810.03422
https://arxiv.org/abs/1810.03422v6
https://arxiv.org/pdf/1810.03422v6.pdf
https://github.com/WTCN-computational-anatomy-group/MTVprocess3D
false
false
true
none
https://paperswithcode.com/paper/it-is-not-as-good-as-you-think-evaluating
It is Not as Good as You Think! Evaluating Simultaneous Machine Translation on Interpretation Data
2110.05213
https://arxiv.org/abs/2110.05213v1
https://arxiv.org/pdf/2110.05213v1.pdf
https://github.com/mingzi151/interpretationdata
true
true
false
none
https://paperswithcode.com/paper/shape-error-modelling-and-simulation-of-3d
Object shape error modelling and simulation during early design stage by morphing Gaussian Random Fields
2010.14889
https://arxiv.org/abs/2010.14889v2
https://arxiv.org/pdf/2010.14889v2.pdf
https://github.com/manojkumrb/MGRF_Source
true
false
false
none
https://paperswithcode.com/paper/neural-stored-program-memory
Neural Stored-program Memory
1906.08862
https://arxiv.org/abs/1906.08862v2
https://arxiv.org/pdf/1906.08862v2.pdf
https://github.com/thaihungle/NSM
true
false
true
pytorch
https://paperswithcode.com/paper/reinforcement-learning-via-recurrent
Reinforcement Learning via Recurrent Convolutional Neural Networks
1701.02392
http://arxiv.org/abs/1701.02392v1
http://arxiv.org/pdf/1701.02392v1.pdf
https://github.com/tanmayshankar/RCNN_MDP
true
true
true
none
https://paperswithcode.com/paper/resdepth-learned-residual-stereo
ResDepth: Learned Residual Stereo Reconstruction
2001.08026
https://arxiv.org/abs/2001.08026v3
https://arxiv.org/pdf/2001.08026v3.pdf
https://github.com/stuckerc/ResDepth
true
false
false
pytorch
https://paperswithcode.com/paper/pilot-study-for-the-cost-action-reassembling
Pilot study for the COST Action "Reassembling the Republic of Letters": language-driven network analysis of letters from the Hartlib's Papers
1801.09896
http://arxiv.org/abs/1801.09896v1
http://arxiv.org/pdf/1801.09896v1.pdf
https://github.com/kercos/DH_Code
true
true
false
none
https://paperswithcode.com/paper/polysemy-deciphering-network-for-human-object
Polysemy Deciphering Network for Human-Object Interaction Detection
null
https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3382_ECCV_2020_paper.php
https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650069.pdf
https://github.com/MuchHair/PD-Net
true
true
false
none
https://paperswithcode.com/paper/gikt-a-graph-based-interaction-model-for
GIKT: A Graph-based Interaction Model for Knowledge Tracing
2009.05991
https://arxiv.org/abs/2009.05991v1
https://arxiv.org/pdf/2009.05991v1.pdf
https://github.com/apexedm/gikt
false
false
true
tf
https://paperswithcode.com/paper/kalmanbot-kalmannet-aided-bollinger-bands-for
Neural Augmented Kalman Filtering with Bollinger Bands for Pairs Trading
2210.15448
https://arxiv.org/abs/2210.15448v2
https://arxiv.org/pdf/2210.15448v2.pdf
https://github.com/kalmannet/kalmanbot_icassp23
true
true
false
pytorch
https://paperswithcode.com/paper/recod-titans-at-isic-challenge-2017
RECOD Titans at ISIC Challenge 2017
1703.04819
http://arxiv.org/abs/1703.04819v1
http://arxiv.org/pdf/1703.04819v1.pdf
https://github.com/learningtitans/isbi2017-part3
true
true
true
tf
https://paperswithcode.com/paper/a-simple-approach-to-sparse-clustering
A Simple Approach to Sparse Clustering
1602.07277
http://arxiv.org/abs/1602.07277v2
http://arxiv.org/pdf/1602.07277v2.pdf
https://github.com/victorpu/SAS_Hill_Climb
true
true
false
none
https://paperswithcode.com/paper/gans-trained-by-a-two-time-scale-update-rule
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
1706.08500
http://arxiv.org/abs/1706.08500v6
http://arxiv.org/pdf/1706.08500v6.pdf
https://github.com/raahii/video-gans-evaluation
false
false
true
pytorch
https://paperswithcode.com/paper/dr-top-k-delegate-centric-top-k-on-gpus
Dr. Top-k: Delegate-Centric Top-k on GPUs
2109.08219
https://arxiv.org/abs/2109.08219v1
https://arxiv.org/pdf/2109.08219v1.pdf
https://github.com/Anil-Gaihre/DrTopKSC
true
false
false
none
https://paperswithcode.com/paper/stargan-unified-generative-adversarial
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
1711.09020
http://arxiv.org/abs/1711.09020v3
http://arxiv.org/pdf/1711.09020v3.pdf
https://github.com/yunjey/StarGAN
false
false
true
pytorch
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/natanielruiz/android-yolo
false
false
true
tf
https://paperswithcode.com/paper/manifold-mixup-learning-better
Manifold Mixup: Learning Better Representations by Interpolating Hidden States
null
https://openreview.net/forum?id=rJlRKjActQ
https://openreview.net/pdf?id=rJlRKjActQ
https://github.com/vikasverma1077/manifold_mixup
false
false
false
pytorch
https://paperswithcode.com/paper/texturegan-controlling-deep-image-synthesis
TextureGAN: Controlling Deep Image Synthesis with Texture Patches
1706.02823
http://arxiv.org/abs/1706.02823v3
http://arxiv.org/pdf/1706.02823v3.pdf
https://github.com/janesjanes/Pytorch-TextureGAN
false
false
true
pytorch
https://paperswithcode.com/paper/diverse-image-to-image-translation-via
Diverse Image-to-Image Translation via Disentangled Representations
1808.00948
http://arxiv.org/abs/1808.00948v1
http://arxiv.org/pdf/1808.00948v1.pdf
https://github.com/Bingwen-Hu/DRIT
false
false
true
pytorch
https://paperswithcode.com/paper/the-one-hundred-layers-tiramisu-fully
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
1611.09326
http://arxiv.org/abs/1611.09326v3
http://arxiv.org/pdf/1611.09326v3.pdf
https://github.com/demul/image_segmentation_project
false
false
true
tf
https://paperswithcode.com/paper/a-users-guide-to-carskit
A User's Guide to CARSKit
1511.03780
http://arxiv.org/abs/1511.03780v2
http://arxiv.org/pdf/1511.03780v2.pdf
https://github.com/abnersuniga/CARSKit-pibic
false
false
true
tf
https://paperswithcode.com/paper/planck-2015-results-xv-gravitational-lensing
Planck 2015 results. XV. Gravitational lensing
1502.01591
http://arxiv.org/abs/1502.01591v3
http://arxiv.org/pdf/1502.01591v3.pdf
https://github.com/abaleato/curved_sky_B_template
false
false
true
none
https://paperswithcode.com/paper/clearing-noisy-annotations-for-computed
Clearing noisy annotations for computed tomography imaging
1807.09151
http://arxiv.org/abs/1807.09151v1
http://arxiv.org/pdf/1807.09151v1.pdf
https://github.com/analysiscenter/radio
true
true
false
none
https://paperswithcode.com/paper/exploring-the-structure-of-a-real-time
Exploring the structure of a real-time, arbitrary neural artistic stylization network
1705.06830
http://arxiv.org/abs/1705.06830v2
http://arxiv.org/pdf/1705.06830v2.pdf
https://github.com/taivu1998/GANime
false
false
true
tf
https://paperswithcode.com/paper/yolo9000-better-faster-stronger
YOLO9000: Better, Faster, Stronger
1612.08242
http://arxiv.org/abs/1612.08242v1
http://arxiv.org/pdf/1612.08242v1.pdf
https://github.com/mdv3101/darknet-yolov3
false
false
true
none
https://paperswithcode.com/paper/a-neural-algorithm-of-artistic-style
A Neural Algorithm of Artistic Style
1508.06576
http://arxiv.org/abs/1508.06576v2
http://arxiv.org/pdf/1508.06576v2.pdf
https://github.com/taivu1998/GANime
false
false
true
tf
https://paperswithcode.com/paper/integrative-multi-view-reduced-rank
Integrative Multi-View Reduced-Rank Regression: Bridging Group-Sparse and Low-Rank Models
1807.10375
http://arxiv.org/abs/1807.10375v1
http://arxiv.org/pdf/1807.10375v1.pdf
https://github.com/reagan0323/iRRR
true
true
false
none
https://paperswithcode.com/paper/non-zeeman-circular-polarization-of-molecular
Non-Zeeman Circular Polarization of Molecular Spectral Lines in the ISM
1808.00211
http://arxiv.org/abs/1808.00211v1
http://arxiv.org/pdf/1808.00211v1.pdf
https://github.com/mef51/CPisCommon
false
false
true
none
https://paperswithcode.com/paper/photometry-of-very-bright-stars-with-kepler
Photometry of Very Bright Stars with Kepler and K2 Smear Data
1510.00008
http://arxiv.org/abs/1510.00008v1
http://arxiv.org/pdf/1510.00008v1.pdf
https://github.com/benjaminpope/keplersmear
false
false
true
none
https://paperswithcode.com/paper/unsupervised-metric-learning-in-presence-of
Unsupervised Metric Learning in Presence of Missing Data
1807.07610
http://arxiv.org/abs/1807.07610v3
http://arxiv.org/pdf/1807.07610v3.pdf
https://github.com/rsonthal/MRMissing.jl
true
false
true
none
https://paperswithcode.com/paper/assessing-binary-classifiers-using-only
Assessing binary classifiers using only positive and unlabeled data
1504.06837
http://arxiv.org/abs/1504.06837v2
http://arxiv.org/pdf/1504.06837v2.pdf
https://github.com/claesenm/semisup-metrics
false
false
true
none
https://paperswithcode.com/paper/a-new-anew-evaluation-of-a-word-list-for
A new ANEW: Evaluation of a word list for sentiment analysis in microblogs
1103.2903
http://arxiv.org/abs/1103.2903v1
http://arxiv.org/pdf/1103.2903v1.pdf
https://github.com/syzer/sentiment-analyser
false
false
true
none
https://paperswithcode.com/paper/optimizing-event-selection-with-the-random
Optimizing Event Selection with the Random Grid Search
1706.09907
http://arxiv.org/abs/1706.09907v2
http://arxiv.org/pdf/1706.09907v2.pdf
https://github.com/ShortTrackSusy/ShortTrackSusy
false
false
true
none
https://paperswithcode.com/paper/assessing-gender-bias-in-machine-translation
Assessing Gender Bias in Machine Translation -- A Case Study with Google Translate
1809.02208
http://arxiv.org/abs/1809.02208v4
http://arxiv.org/pdf/1809.02208v4.pdf
https://github.com/marceloprates/Gender-Bias
true
true
false
none
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/CryptoSalamander/pytorch_paper_implementation
false
false
true
pytorch
https://paperswithcode.com/paper/validating-uncertainty-in-medical-image
Validating uncertainty in medical image translation
2002.04639
https://arxiv.org/abs/2002.04639v1
https://arxiv.org/pdf/2002.04639v1.pdf
https://github.com/jcreinhold/uncertaintorch
true
false
false
pytorch
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/machine-reasoning-ufrgs/typed-graph-network
false
false
true
tf
https://paperswithcode.com/paper/end-to-end-text-dependent-speaker
End-to-End Text-Dependent Speaker Verification
1509.08062
http://arxiv.org/abs/1509.08062v1
http://arxiv.org/pdf/1509.08062v1.pdf
https://github.com/dalonlobo/diarization-experiments
false
false
true
tf
https://paperswithcode.com/paper/repulsion-loss-detecting-pedestrians-in-a
Repulsion Loss: Detecting Pedestrians in a Crowd
1711.07752
http://arxiv.org/abs/1711.07752v2
http://arxiv.org/pdf/1711.07752v2.pdf
https://github.com/bailvwangzi/repulsion_loss_ssd
false
false
true
pytorch
https://paperswithcode.com/paper/real-time-self-adaptive-deep-stereo
Real-time self-adaptive deep stereo
1810.05424
http://arxiv.org/abs/1810.05424v2
http://arxiv.org/pdf/1810.05424v2.pdf
https://github.com/CVLAB-Unibo/Real-time-self-adaptive-deep-stereo
true
true
true
tf
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/huan123/py-fatser-rcnn
false
false
true
tf
https://paperswithcode.com/paper/ssd-single-shot-multibox-detector
SSD: Single Shot MultiBox Detector
1512.02325
http://arxiv.org/abs/1512.02325v5
http://arxiv.org/pdf/1512.02325v5.pdf
https://github.com/bailvwangzi/repulsion_loss_ssd
false
false
true
pytorch
https://paperswithcode.com/paper/convolutional-neural-networks-for-sentence
Convolutional Neural Networks for Sentence Classification
1408.5882
http://arxiv.org/abs/1408.5882v2
http://arxiv.org/pdf/1408.5882v2.pdf
https://github.com/shagunsodhani/CNN-Sentence-Classifier
false
false
true
none
https://paperswithcode.com/paper/labelfusion-a-pipeline-for-generating-ground
LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes
1707.04796
http://arxiv.org/abs/1707.04796v3
http://arxiv.org/pdf/1707.04796v3.pdf
https://github.com/RobotLocomotion/LabelFusion
false
false
true
tf
https://paperswithcode.com/paper/tensorflow-distributions
TensorFlow Distributions
1711.10604
http://arxiv.org/abs/1711.10604v1
http://arxiv.org/pdf/1711.10604v1.pdf
https://github.com/nicola-decao/s-vae-tf
false
false
true
tf
https://paperswithcode.com/paper/genetic-algorithm-based-polar-code
Genetic Algorithm-based Polar Code Construction for the AWGN Channel
1901.06444
http://arxiv.org/abs/1901.06444v1
http://arxiv.org/pdf/1901.06444v1.pdf
https://github.com/AhmedElkelesh/Genetic-Algorithm-based-Polar-Code-Construction
true
true
true
none
https://paperswithcode.com/paper/recovering-quantum-gates-from-few-average
Recovering quantum gates from few average gate fidelities
1803.00572
http://arxiv.org/abs/1803.00572v2
http://arxiv.org/pdf/1803.00572v2.pdf
https://github.com/MartKl/Quantum_process_tomography_with_average_gate_fidelities
true
true
true
none
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/Sshanu/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/Sshanu/AdaptSegNet
false
false
true
pytorch
https://paperswithcode.com/paper/opening-the-black-box-of-deep-neural-networks
Opening the Black Box of Deep Neural Networks via Information
1703.00810
http://arxiv.org/abs/1703.00810v3
http://arxiv.org/pdf/1703.00810v3.pdf
https://github.com/sichen-x/Fashion-MNIST-NN-Modeling-Plotting
false
false
true
tf
https://paperswithcode.com/paper/single-shot-temporal-action-detection
Single Shot Temporal Action Detection
1710.06236
http://arxiv.org/abs/1710.06236v1
http://arxiv.org/pdf/1710.06236v1.pdf
https://github.com/hypjudy/Decouple-SSAD
false
false
true
tf
https://paperswithcode.com/paper/voxelnet-end-to-end-learning-for-point-cloud
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
1711.06396
http://arxiv.org/abs/1711.06396v1
http://arxiv.org/pdf/1711.06396v1.pdf
https://github.com/abdullahozer11/Segmentation-and-Classification-of-Objects-in-Point-Clouds
false
false
true
tf
https://paperswithcode.com/paper/billion-scale-network-embedding-with
Billion-scale Network Embedding with Iterative Random Projection
1805.02396
http://arxiv.org/abs/1805.02396v2
http://arxiv.org/pdf/1805.02396v2.pdf
https://github.com/ZW-ZHANG/RandNE
true
true
false
none
https://paperswithcode.com/paper/niftynet-a-deep-learning-platform-for-medical
NiftyNet: a deep-learning platform for medical imaging
1709.03485
http://arxiv.org/abs/1709.03485v2
http://arxiv.org/pdf/1709.03485v2.pdf
https://github.com/NifTK/NiftyNet
true
true
false
tf
https://paperswithcode.com/paper/mixnet-mixed-depthwise-convolutional-kernels
MixConv: Mixed Depthwise Convolutional Kernels
1907.09595
https://arxiv.org/abs/1907.09595v3
https://arxiv.org/pdf/1907.09595v3.pdf
https://github.com/2023-MindSpore-1/ms-code-19
false
false
false
mindspore
https://paperswithcode.com/paper/reinforcement-learning-for-automatic-test
Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration
1811.04122
http://arxiv.org/abs/1811.04122v1
http://arxiv.org/pdf/1811.04122v1.pdf
https://github.com/codeslord/RLforATCP
false
false
false
none
https://paperswithcode.com/paper/blind-source-extraction-based-on-multi
Target Speech Extraction Based on Blind Source Separation and X-vector-based Speaker Selection Trained with Data Augmentation
2005.07976
https://arxiv.org/abs/2005.07976v2
https://arxiv.org/pdf/2005.07976v2.pdf
https://github.com/annie-gu/MVAEBasedBSE
true
true
false
none
https://paperswithcode.com/paper/speeding-up-reinforcement-learning-based
Speeding up Reinforcement Learning-based Information Extraction Training using Asynchronous Methods
null
https://aclanthology.org/D17-1281
https://aclanthology.org/D17-1281.pdf
https://github.com/adi-sharma/RLIE_A3C
true
true
false
tf
https://paperswithcode.com/paper/coco-cn-for-cross-lingual-image-tagging
COCO-CN for Cross-Lingual Image Tagging, Captioning and Retrieval
1805.08661
http://arxiv.org/abs/1805.08661v2
http://arxiv.org/pdf/1805.08661v2.pdf
https://github.com/evanmiltenburg/COCO-CN-Results-Viewer
false
false
true
none
https://paperswithcode.com/paper/the-urban-last-mile-problem-autonomous-drone
The Urban Last Mile Problem: Autonomous Drone Delivery to Your Balcony
1809.08022
http://arxiv.org/abs/1809.08022v1
http://arxiv.org/pdf/1809.08022v1.pdf
https://github.com/szebedy/autonomous-drone
true
true
true
none
https://paperswithcode.com/paper/neural-general-circulation-models
Neural General Circulation Models for Weather and Climate
2311.07222
https://arxiv.org/abs/2311.07222v3
https://arxiv.org/pdf/2311.07222v3.pdf
https://github.com/google-research/dinosaur
false
false
true
jax
https://paperswithcode.com/paper/fast-small-and-exact-infinite-order-language
Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees
1608.04465
http://arxiv.org/abs/1608.04465v1
http://arxiv.org/pdf/1608.04465v1.pdf
https://github.com/eehsan/cstlm
true
true
false
none
https://paperswithcode.com/paper/neural-structural-correspondence-learning-for
Neural Structural Correspondence Learning for Domain Adaptation
1610.01588
http://arxiv.org/abs/1610.01588v3
http://arxiv.org/pdf/1610.01588v3.pdf
https://github.com/yftah89/Neural-SCLDomain-Adaptation
true
true
false
none
https://paperswithcode.com/paper/spectral-normalization-for-generative
Spectral Normalization for Generative Adversarial Networks
1802.05957
http://arxiv.org/abs/1802.05957v1
http://arxiv.org/pdf/1802.05957v1.pdf
https://github.com/Bingwen-Hu/DRIT
false
false
true
pytorch
https://paperswithcode.com/paper/understanding-boolean-function-learnability
Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models
2009.05908
https://arxiv.org/abs/2009.05908v3
https://arxiv.org/pdf/2009.05908v3.pdf
https://github.com/machine-reasoning-ufrgs/mlbf
true
true
true
none
https://paperswithcode.com/paper/non-local-neural-networks
Non-local Neural Networks
1711.07971
http://arxiv.org/abs/1711.07971v3
http://arxiv.org/pdf/1711.07971v3.pdf
https://github.com/huyz1117/Non_Local_Net_TensorFlow
false
false
true
tf
https://paperswithcode.com/paper/centroid-based-scene-classification-cbsc
Centroid Based Concept Learning for RGB-D Indoor Scene Classification
1911.00155
https://arxiv.org/abs/1911.00155v4
https://arxiv.org/pdf/1911.00155v4.pdf
https://github.com/aliayub7/CBCL_RGBD
true
true
true
pytorch
https://paperswithcode.com/paper/squeezeseg-convolutional-neural-nets-with
SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud
1710.07368
http://arxiv.org/abs/1710.07368v1
http://arxiv.org/pdf/1710.07368v1.pdf
https://github.com/BichenWuUCB/SqueezeSeg
false
false
true
tf
https://paperswithcode.com/paper/sickle-a-multi-sensor-satellite-imagery
SICKLE: A Multi-Sensor Satellite Imagery Dataset Annotated with Multiple Key Cropping Parameters
2312.00069
https://arxiv.org/abs/2312.00069v1
https://arxiv.org/pdf/2312.00069v1.pdf
https://github.com/Depanshu-Sani/SICKLE
true
false
false
pytorch
https://paperswithcode.com/paper/disentangled-representation-learning-for-non
Disentangled Representation Learning for Non-Parallel Text Style Transfer
1808.04339
http://arxiv.org/abs/1808.04339v2
http://arxiv.org/pdf/1808.04339v2.pdf
https://github.com/h3lio5/linguistic-style-transfer-pytorch
false
false
false
pytorch
https://paperswithcode.com/paper/simplex-representation-for-subspace
Scaled Simplex Representation for Subspace Clustering
1807.09930
https://arxiv.org/abs/1807.09930v3
https://arxiv.org/pdf/1807.09930v3.pdf
https://github.com/csjunxu/SRSC
false
false
true
none
https://paperswithcode.com/paper/impact-industrial-machine-perception-via
IMPACT: Industrial Machine Perception via Acoustic Cognitive Transformer
2507.06481
https://arxiv.org/abs/2507.06481v1
https://arxiv.org/pdf/2507.06481v1.pdf
https://github.com/hanprd/IMPACT
true
true
true
pytorch
https://paperswithcode.com/paper/going-deeper-with-convolutions
Going Deeper with Convolutions
1409.4842
http://arxiv.org/abs/1409.4842v1
http://arxiv.org/pdf/1409.4842v1.pdf
https://github.com/deepmind/kinetics-i3d
false
false
true
tf
https://paperswithcode.com/paper/tighter-low-rank-approximation-via-sampling
Tighter Low-rank Approximation via Sampling the Leveraged Element
1410.3886
http://arxiv.org/abs/1410.3886v1
http://arxiv.org/pdf/1410.3886v1.pdf
https://github.com/wushanshan/MatrixProductPCA
false
false
true
none
https://paperswithcode.com/paper/deepdiva-a-highly-functional-python-framework
DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments
1805.00329
http://arxiv.org/abs/1805.00329v1
http://arxiv.org/pdf/1805.00329v1.pdf
https://github.com/dusan312/HandM
false
false
true
pytorch
https://paperswithcode.com/paper/efficient-neural-network-robustness
Efficient Neural Network Robustness Certification with General Activation Functions
1811.00866
http://arxiv.org/abs/1811.00866v1
http://arxiv.org/pdf/1811.00866v1.pdf
https://github.com/huanzhang12/CROWN-Robustness-Certification
true
true
true
tf
https://paperswithcode.com/paper/detecting-spacecraft-anomalies-using-lstms
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
1802.04431
http://arxiv.org/abs/1802.04431v3
http://arxiv.org/pdf/1802.04431v3.pdf
https://github.com/akshu281/KDD_LSTM
false
false
true
tf