NeurIPS

2021–2025 確定版

著者一覧 · 国際会議 · 大学ランキング

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Machine Learning

2021 · 2,334 papers

このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。

2021 · NeurIPS
Scalable Neural Data Server: A Data Recommender for Transfer Learning
Tianshi Cao, Sasha (Alexandre) Doubov, David Acuna, Sanja Fidler
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scalable Online Planning via Reinforcement Learning Fine-Tuning
Arnaud Fickinger, Hengyuan Hu, Brandon Amos, Stuart J. Russell, Noam Brown
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scalable Quasi-Bayesian Inference for Instrumental Variable Regression
Ziyu Wang, Yuhao Zhou, Tongzheng Ren, Jun Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scalable Rule-Based Representation Learning for Interpretable Classification
Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scalable Thompson Sampling using Sparse Gaussian Process Models
Sattar Vakili, Henry Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scalable and Stable Surrogates for Flexible Classifiers with Fairness Constraints
Henry C Bendekgey, Erik B. Sudderth
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scalars are universal: Equivariant machine learning, structured like classical physics
Soledad Villar, David W Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers
Husheng Han, Kaidi Xu, Xing Hu, Xiaobing Chen, Ling LIANG, Zidong Du, Qi Guo, Yanzhi Wang, Yunji Chen
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets
Max Ryabinin, Andrey Malinin, Mark Gales
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scaling Gaussian Processes with Derivative Information Using Variational Inference
Misha Padidar, Xinran Zhu, Leo Huang, Jacob Gardner, David Bindel
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scaling Neural Tangent Kernels via Sketching and Random Features
Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scaling Up Exact Neural Network Compression by ReLU Stability
Thiago Serra, Xin Yu, Abhinav Kumar, Srikumar Ramalingam
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scaling Vision with Sparse Mixture of Experts
Carlos Riquelme, Joan Puigcerver, Basil Mustafa, Maxim Neumann, Rodolphe Jenatton, André Susano Pinto, Daniel Keysers, Neil Houlsby
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
Alkis Gotovos, Rebekka Burkholz, John Quackenbush, Stefanie Jegelka
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning
Jiani Huang, Ziyang Li, Binghong Chen, Karan Samel, Mayur Naik, Le Song, Xujie Si
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scatterbrain: Unifying Sparse and Low-rank Attention
Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Scheduling jobs with stochastic holding costs
Dabeen Lee, Milan Vojnovic
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Score-based Generative Modeling in Latent Space
Arash Vahdat, Karsten Kreis, Jan Kautz
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Score-based Generative Neural Networks for Large-Scale Optimal Transport
Mara Daniels, Tyler Maunu, Paul Hand
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Searching Parameterized AP Loss for Object Detection
Tao Chenxin, Zizhang Li, Xizhou Zhu, Gao Huang, Yong Liu, jifeng dai
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Searching for Efficient Transformers for Language Modeling
David So, Wojciech Mańke, Hanxiao Liu, Zihang Dai, Noam Shazeer, Quoc V Le
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Searching the Search Space of Vision Transformer
Minghao Chen, Kan Wu, Bolin Ni, Houwen Peng, Bei Liu, Jianlong Fu, Hongyang Chao, Haibin Ling
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Second-Order Neural ODE Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
See More for Scene: Pairwise Consistency Learning for Scene Classification
Gongwei Chen, Xinhang Song, Bohan Wang, Shuqiang Jiang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Selective Sampling for Online Best-arm Identification
Romain Camilleri, Zhihan Xiong, Maryam Fazel, Lalit Jain, Kevin G. Jamieson
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Adaptable Point Processes with Nonparametric Time Decays
Zhimeng Pan, Zheng Wang, Jeff M Phillips, Shandian Zhe
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
Jannik Kossen, Neil Band, Clare Lyle, Aidan N Gomez, Thomas Rainforth, Yarin Gal
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Consistent Models and Values
Greg Farquhar, Kate Baumli, Zita Marinho, Angelos Filos, Matteo Hessel, Hado P van Hasselt, David Silver
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks
Jinhee Lee, Haeri Kim, Youngkyu Hong, Hye Won Chung
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Instantiated Recurrent Units with Dynamic Soft Recursion
Aston Zhang, Yi Tay, Yikang Shen, Alvin Chan, SHUAI ZHANG
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Interpretable Model with Transformation Equivariant Interpretation
Yipei Wang, Xiaoqian Wang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels
Jizong Peng, Ping Wang, Christian Desrosiers, Marco Pedersoli
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised Bug Detection and Repair
Miltiadis Allamanis, Henry Jackson-Flux, Marc Brockschmidt
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised GANs with Label Augmentation
Liang Hou, Huawei Shen, Qi Cao, Xueqi Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised Learning Disentangled Group Representation as Feature
Tan Wang, Zhongqi Yue, Jianqiang Huang, Qianru Sun, Hanwang Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks
Jesse Hagenaars, Federico Paredes-Valles, Guido de Croon
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised Learning with Kernel Dependence Maximization
Yazhe Li, Roman Pogodin, Danica J. Sutherland, Arthur Gretton
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised Multi-Object Tracking with Cross-input Consistency
Favyen Bastani, Songtao He, Samuel Madden
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction
Konstantin Schürholt, Dimche Kostadinov, Damian Borth
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning
Hanzhe Hu, Fangyun Wei, Han Hu, Qiwei Ye, Jinshi Cui, Liwei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification
Tong Chen, Jean B Lasserre, Victor Magron, Edouard Pauwels
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics
Carles Domingo i Enrich, Youssef Mroueh
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sequence-to-Sequence Learning with Latent Neural Grammars
Yoon Kim
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sequential Algorithms for Testing Closeness of Distributions
Aadil Oufkir, Omar Fawzi, Nicolas Flammarion, Aurélien Garivier
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sequential Causal Imitation Learning with Unobserved Confounders
Daniel Kumor, Junzhe Zhang, Elias Bareinboim
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Set Prediction in the Latent Space
Konpat Preechakul, Chawan Piansaddhayanon, Burin Naowarat, Tirasan Khandhawit, Sira Sriswasdi, Ekapol Chuangsuwanich
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Settling the Variance of Multi-Agent Policy Gradients
Jakub Grudzien Kuba, Muning Wen, Linghui Meng, shangding gu, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shape As Points: A Differentiable Poisson Solver
Songyou Peng, Chiyu Jiang, Yiyi Liao, Michael Niemeyer, Marc Pollefeys, Andreas Geiger
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shape Registration in the Time of Transformers
Giovanni Trappolini, Luca Cosmo, Luca Moschella, Riccardo Marin, Simone Melzi, Emanuele Rodolà
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects
Denys Rozumnyi, Martin R. Oswald, Vittorio Ferrari, Marc Pollefeys
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shape your Space: A Gaussian Mixture Regularization Approach to Deterministic Autoencoders
Amrutha Saseendran, Kathrin Skubch, Stefan Falkner, Margret Keuper
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shapeshifter: a Parameter-efficient Transformer using Factorized Reshaped Matrices
Aliakbar Panahi, Seyran Saeedi, Tom Arodz
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shaping embodied agent behavior with activity-context priors from egocentric video
Tushar Nagarajan, Kristen Grauman
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shapley Residuals: Quantifying the limits of the Shapley value for explanations
Indra Kumar, Carlos Scheidegger, Suresh Venkatasubramanian, Sorelle Friedler
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shared Independent Component Analysis for Multi-Subject Neuroimaging
Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvarinen
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sharp Impossibility Results for Hyper-graph Testing
Jiashun Jin, Zheng Tracy Ke, Jiajun Liang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shift Invariance Can Reduce Adversarial Robustness
Vasu Singla, Songwei Ge, Basri Ronen, David Jacobs
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data
Qi Zhu, Natalia Ponomareva, Jiawei Han, Bryan Perozzi
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Shifted Chunk Transformer for Spatio-Temporal Representational Learning
Xuefan Zha, Wentao Zhu, Lv Xun, Sen Yang, Ji Liu
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sifting through the noise: Universal first-order methods for stochastic variational inequalities
Kimon Antonakopoulos, Thomas Pethick, Ali Kavis, Panayotis Mertikopoulos, Volkan Cevher
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sim and Real: Better Together
Shirli Di-Castro, Dotan Di Castro, Shie Mannor
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement
Heyang Qin, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Similarity and Matching of Neural Network Representations
Adrián Csiszárik, Péter Kőrösi-Szabó, Ákos Matszangosz, Gergely Papp, Dániel Varga
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning
ZHENHUAN YANG, Yunwen Lei, Puyu Wang, Tianbao Yang, Yiming Ying
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions
Alejandro Carderera, Mathieu Besançon, Sebastian Pokutta
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
Koby Bibas, Meir Feder, Tal Hassner
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
SketchGen: Generating Constrained CAD Sketches
Wamiq Para, Shariq Bhat, Paul Guerrero, Tom Kelly, Niloy Mitra, Leonidas Guibas, Peter Wonka
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Skipping the Frame-Level: Event-Based Piano Transcription With Neural Semi-CRFs
Yujia Yan, Frank Cwitkowitz, Zhiyao Duan
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method
Yifan Chen, Qi Zeng, Heng Ji, Yun Yang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Slice Sampling Reparameterization Gradients
David Zoltowski, Diana Cai, Ryan P. Adams
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sliced Mutual Information: A Scalable Measure of Statistical Dependence
Ziv Goldfeld, Kristjan Greenewald
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang, Yun Fu
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction
Dominik Stöger, Mahdi Soltanolkotabi
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Smooth Bilevel Programming for Sparse Regularization
Clarice Poon, Gabriel Peyré
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Smooth Normalizing Flows
Jonas Köhler, Andreas Krämer, Frank Noe
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness
Jongheon Jeong, Sejun Park, Minkyu Kim, Heung-Chang Lee, Do-Guk Kim, Jinwoo Shin
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Smoothness Matrices Beat Smoothness Constants: Better Communication Compression Techniques for Distributed Optimization
Mher Safaryan, Filip Hanzely, Peter Richtarik
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing
Charles Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Soft Calibration Objectives for Neural Networks
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael Mozer, Becca Roelofs
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Solving Graph-based Public Goods Games with Tree Search and Imitation Learning
Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent
Emmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Georgios Piliouras
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Solving Soft Clustering Ensemble via $k$-Sparse Discrete Wasserstein Barycenter
Ruizhe Qin, Mengying Li, Hu Ding
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Space-time Mixing Attention for Video Transformer
Adrian Bulat, Juan Manuel Perez Rua, Swathikiran Sudhakaran, Brais Martinez, Georgios Tzimiropoulos
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration
Yan Sun, Wenjun Xiong, Faming Liang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse Flows: Pruning Continuous-depth Models
Lucas Liebenwein, Ramin Hasani, Alexander Amini, Daniela Rus
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation
Florian Bernard, Daniel Cremers, Johan Thunberg
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse Spiking Gradient Descent
Nicolas Perez-Nieves, Dan Goodman
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space
Jiehong Lin, Hongyang Li, Ke Chen, Jiangbo Lu, Kui Jia
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
Shiwei Liu, Tianlong Chen, Xiaohan Chen, Zahra Atashgahi, Lu Yin, Huanyu Kou, Li Shen, Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse Uncertainty Representation in Deep Learning with Inducing Weights
Hippolyt Ritter, Martin Kukla, Cheng Zhang, Yingzhen Li
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparse is Enough in Scaling Transformers
Sebastian Jaszczur, Aakanksha Chowdhery, Afroz Mohiuddin, LUKASZ KAISER, Wojciech Gajewski, Henryk Michalewski, Jonni Kanerva
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains
Christian Gumbsch, Martin V. Butz, Georg Martius
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework
Tengteng Huang, Yifan Sun, Xun Wang, Haotian Yao, Chi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis
Yutong He, Dingjie Wang, Nicholas Lai, William Zhang, Chenlin Meng, Marshall Burke, David Lobell, Stefano Ermon
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Spatio-Temporal Variational Gaussian Processes
Oliver Hamelijnck, William Wilkinson, Niki Loppi, Arno Solin, Theodoros Damoulas
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks
Zichen Miao, Ze Wang, Xiuyuan Cheng, Qiang Qiu
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Spectral embedding for dynamic networks with stability guarantees
Ian Gallagher, Andrew Jones, Patrick Rubin-Delanchy
Machine Learning
日本大学: 関与なし（対象大学）
2021 · NeurIPS
Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution
Guangpin Tao, Xiaozhong Ji, Wenzhuo Wang, Shuo Chen, Chuming Lin, Yun Cao, Tong Lu, Donghao Luo, Ying Tai
Machine Learning
日本大学: 関与なし（対象大学）