NeurIPS

2022–2026 LIVE

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Machine Learning

2023 · 3,218 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。

2023 · NeurIPS
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations
Chiyu Ma, Brandon Zhao, Chaofan Chen, Cynthia Rudin
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Thought Cloning: Learning to Think while Acting by Imitating Human Thinking
Shengran Hu, Jeff Clune
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Three Iterations of (d − 1)-WL Test Distinguish Non Isometric Clouds of d-dimensional Points
Valentino Delle Rose, Alexander Kozachinskiy, Cristobal Rojas, Mircea Petrache, Pablo Barceló
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Three Towers: Flexible Contrastive Learning with Pretrained Image Models
Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance
Lisha Chen, Heshan Fernando, Yiming Ying, Tianyi Chen
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Thrust: Adaptively Propels Large Language Models with External Knowledge
Xinran Zhao, Hongming Zhang, Xiaoman Pan, Wenlin Yao, Dong Yu, Jianshu Chen
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Tight Bounds for Volumetric Spanners and Applications
Aditya Bhaskara, Sepideh Mahabadi, Ali Vakilian
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Tight Risk Bounds for Gradient Descent on Separable Data
Matan Schliserman, Tomer Koren
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Time Series Kernels based on Nonlinear Vector AutoRegressive Delay Embeddings
Giovanni De Felice, John Goulermas, Vladimir Gusev
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Time Series as Images: Vision Transformer for Irregularly Sampled Time Series
Zekun Li, Shiyang Li, Xifeng Yan
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Time-Independent Information-Theoretic Generalization Bounds for SGLD
Futoshi Futami, Masahiro Fujisawa
Machine Learning
日本大学: 大阪大学
2023 · NeurIPS
Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value
Jaeyeon Kim, Asuman Ozdaglar, Chanwoo Park, Ernest Ryu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Time-uniform confidence bands for the CDF under nonstationarity
Paul Mineiro, Steven Howard
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
Leon Klein, Andrew Foong, Tor Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noe, Ryota Tomioka
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis
Fuzhao Xue, Yao Fu, Wangchunshu Zhou, Zangwei Zheng, Yang You
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P Vetrov, Ekaterina Lobacheva
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Token-Scaled Logit Distillation for Ternary Weight Generative Language Models
Minsoo Kim, Sihwa Lee, Janghwan Lee, Sukjin Hong, Du-Seong Chang, Wonyong Sung, Jungwook Choi
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Toolformer: Language Models Can Teach Themselves to Use Tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessi, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
Shibo Hao, Tianyang Liu, Zhen Wang, Zhiting Hu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Tools for Verifying Neural Models' Training Data
Dami Choi, Yonadav Shavit, David K. Duvenaud
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Top-Ambiguity Samples Matter: Understanding Why Deep Ensemble Works in Selective Classification
Qiang Ding, Yixuan Cao, Ping Luo
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models
Pum Jun Kim, Yoojin Jang, Jisu Kim, Jaejun Yoo
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
TopoSRL: Topology preserving self-supervised Simplicial Representation Learning
Hiren Madhu, Sundeep Prabhakar Chepuri
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Topological Obstructions and How to Avoid Them
Babak Esmaeili, Robin Walters, Heiko Zimmermann, Jan-Willem van de Meent
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Topological Parallax: A Geometric Specification for Deep Perception Models
Abraham Smith, Michael Catanzaro, Gabrielle Angeloro, Nirav Patel, Paul Bendich
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Topological RANSAC for instance verification and retrieval without fine-tuning
Guoyuan An, Ju-hyeong Seon, Inkyu An, Yuchi Huo, Sung-eui Yoon
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Topology-Aware Uncertainty for Image Segmentation
Saumya Gupta, Yikai Zhang, Xiaoling Hu, Prateek Prasanna, Chao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms
Sijia Zhou, Yunwen Lei, Ata Kaban
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Toward Re-Identifying Any Animal
Bingliang Jiao, Lingqiao Liu, Liying Gao, Ruiqi Wu, Guosheng Lin, PENG WANG, Yanning Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Toward Understanding Generative Data Augmentation
Chenyu Zheng, Guoqiang Wu, Chongxuan LI
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards A Richer 2D Understanding of Hands at Scale
Tianyi Cheng, Dandan Shan, Ayda Hassen, Richard Higgins, David Fouhey
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Accelerated Model Training via Bayesian Data Selection
Zhijie Deng, Peng Cui, Jun Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity
Metod Jazbec, James Allingham, Dan Zhang, Eric Nalisnick
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Automated Circuit Discovery for Mechanistic Interpretability
Arthur Conmy, Augustine Mavor-Parker, Aengus Lynch, Stefan Heimersheim, Adrià Garriga-Alonso
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Better Dynamic Graph Learning: New Architecture and Unified Library
Le Yu, Leilei Sun, Bowen Du, Weifeng Lv
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
Hedi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach
Phillip Pope, David Jacobs
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Consistent Video Editing with Text-to-Image Diffusion Models
Zicheng Zhang, Bonan Li, Xuecheng Nie, Congying Han, Tiande Guo, Luoqi Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask?
Hoang Pham, The Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le, Hongkai Wen, Long Tran-Thanh
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
Jing Xu, Jiaye Teng, Yang Yuan, Andrew Yao
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Distribution-Agnostic Generalized Category Discovery
Jianhong Bai, Zuozhu Liu, Hualiang Wang, Ruizhe Chen, Lianrui Mu, Xiaomeng Li, Joey Tianyi Zhou, YANG FENG, Jian Wu, Haoji Hu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Efficient Image Compression Without Autoregressive Models
Muhammad Salman Ali, Yeongwoong Kim, Maryam Qamar, Sung-Chang Lim, Donghyun Kim, Chaoning Zhang, Sung-Ho Bae, Hui Yong Kim
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Efficient Pre-Trained Language Model via Feature Correlation Distillation
Kun Huang, Xin Guo, Meng Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Efficient and Accurate Winograd Convolution via Full Quantization
Tianqi Chen, Weixiang Xu, Weihan Chen, Peisong Wang, Jian Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly
Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Shashank Subramanian, Peter Harrington, Kurt Keutzer, Wahid Bhimji, Dmitriy Morozov, Michael W. Mahoney, Amir Gholami
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Free Data Selection with General-Purpose Models
Yichen Xie, Mingyu Ding, Masayoshi TOMIZUKA, Wei Zhan
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
Haonan Wang, Xiaomeng Li
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Higher Ranks via Adversarial Weight Pruning
Yuchuan Tian, Hanting Chen, Tianyu Guo, Chao Xu, Yunhe Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network
Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Weihong Luo, Liang Chen, xiuqiang He, Xue (Steve) Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards In-context Scene Understanding
Ivana Balazevic, David Steiner, Nikhil Parthasarathy, Relja Arandjelović, Olivier Henaff
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Label Position Bias in Graph Neural Networks
Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu Aggarwal, Jiliang Tang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Label-free Scene Understanding by Vision Foundation Models
Runnan Chen, Youquan Liu, Lingdong Kong, Nenglun Chen, Xinge ZHU, Yuexin Ma, Tongliang Liu, Wenping Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Last-layer Retraining for Group Robustness with Fewer Annotations
Tyler LaBonte, Vidya Muthukumar, Abhishek Kumar
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Optimal Caching and Model Selection for Large Model Inference
Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark Barrett, Michael I. Jordan, Jiantao Jiao
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Optimal Effective Resistance Estimation
Rajat Vadiraj Dwaraknath, Ishani Karmarkar, Aaron Sidford
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Personalized Federated Learning via Heterogeneous Model Reassembly
Jiaqi Wang, Xingyi Yang, Suhan Cui, Liwei Che, Lingjuan Lyu, Dongkuan (DK) Xu, Fenglong Ma
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective
Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Robust and Expressive Whole-body Human Pose and Shape Estimation
Hui En Pang, Zhongang Cai, Lei Yang, Qingyi Tao, Zhonghua Wu, Tianwei Zhang, Ziwei Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Self-Interpretable Graph-Level Anomaly Detection
Yixin Liu, Kaize Ding, Qinghua Lu, Fuyi Li, Leo Yu Zhang, Shirui Pan
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning
Chang Lu, Chandan Reddy, Ping Wang, Yue Ning
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Stable Backdoor Purification through Feature Shift Tuning
Rui Min, Zeyu Qin, Li Shen, Minhao Cheng
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Symmetry-Aware Generation of Periodic Materials
Youzhi Luo, Chengkai Liu, Shuiwang Ji
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Test-Time Refusals via Concept Negation
Peiran Dong, Song Guo, Junxiao Wang, Bingjie WANG, Jiewei Zhang, Ziming Liu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Unbounded Machine Unlearning
Meghdad Kurmanji, Peter Triantafillou, Jamie Hayes, Eleni Triantafillou
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent
Tianle Liu, Promit Ghosal, Krishnakumar Balasubramanian, Natesh Pillai
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift
Xingdong Feng, Xin HE, Caixing Wang, Chao Wang, Jingnan Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Stefan Matthes, Zhiwei Han, Hao Shen
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Biagio La Rosa, Leilani Gilpin, Roberto Capobianco
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards robust and generalizable representations of extracellular data using contrastive learning
Ankit Vishnubhotla, Charlotte Loh, Akash Srivastava, Liam Paninski, Cole Hurwitz
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities
Dongrui Liu, Huiqi Deng, Xu Cheng, Qihan Ren, Kangrui Wang, Quanshi Zhang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Tracking Most Significant Shifts in Nonparametric Contextual Bandits
Joe Suk, Samory Kpotufe
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Tracr: Compiled Transformers as a Laboratory for Interpretability
David Lindner, Janos Kramar, Sebastian Farquhar, Matthew Rahtz, Tom McGrath, Vladimir Mikulik
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Trade-off Between Efficiency and Consistency for Removal-based Explanations
Yifan Zhang, Haowei He, Zhiquan Tan, Yang Yuan
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Trading-off price for data quality to achieve fair online allocation
Mathieu Molina, Nicolas Gast, Patrick Loiseau, Vianney Perchet
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Train 'n Trade: Foundations of Parameter Markets
Tzu-Heng Huang, Harit Vishwakarma, Frederic Sala
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models
Yubin Shi, Yixuan Chen, Mingzhi Dong, Xiaochen Yang, Dongsheng Li, Yujiang Wang, Robert Dick, Qin Lv, Yingying Zhao, Fan Yang, Tun Lu, Ning Gu, Li Shang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Train Hard, Fight Easy: Robust Meta Reinforcement Learning
Ido Greenberg, Shie Mannor, Gal Chechik, Eli Meirom
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks
Jun Yin, Chaozhuo Li, Hao Yan, Jianxun Lian, Senzhang Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
Shenzhi Wang, Qisen Yang, Jiawei Gao, Matthieu Lin, HAO CHEN, Liwei Wu, Ning Jia, Shiji Song, Gao Huang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Chain-of-Thought via Latent-Variable Inference
Du Phan, Matthew Douglas Hoffman, David Dohan, Sholto Douglas, Tuan Anh Le, Aaron Parisi, Pavel Sountsov, Charles A. Sutton, Sharad Vikram, Rif A. Saurous
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Energy-Based Normalizing Flow with Score-Matching Objectives
Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete
Daniel Bertschinger, Christoph Hertrich, Paul Jungeblut, Tillmann Miltzow, Simon Weber
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Neural Networks is NP-Hard in Fixed Dimension
Vincent Froese, Christoph Hertrich
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Private Models That Know What They Don’t Know
Stephan Rabanser, Anvith Thudi, Abhradeep Guha Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Transformers with 4-bit Integers
Haocheng Xi, ChangHao Li, Jianfei Chen, Jun Zhu
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Transitive and Commutative Multimodal Transformers with LoReTTa
Manuel Tran, Yashin Dicente Cid, Amal Lahiani, Fabian J. Theis, Tingying Peng, Eldad Klaiman
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function
man zhou, Naishan Zheng, Yuan Xu, Chun-Le Guo, Chongyi Li
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies
Wayne Soo, Vishwa Goudar, Xiao-Jing Wang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training neural operators to preserve invariant measures of chaotic attractors
Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training on Foveated Images Improves Robustness to Adversarial Attacks
Muhammad Shah, Aqsa Kashaf, Bhiksha Raj
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign?
Erin George, Michael Murray, William Swartworth, Deanna Needell
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesis
Zhiyu Jin, Xuli Shen, Bin Li, Xiangyang Xue
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory
Minhak Song, Chulhee Yun
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Trans-Dimensional Generative Modeling via Jump Diffusion Models
Andrew Campbell, William Harvey, Christian Weilbach, Valentin De Bortoli, Thomas Rainforth, Arnaud Doucet
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
TransHP: Image Classification with Hierarchical Prompting
Wenhao Wang, Yifan Sun, Wei Li, Yi Yang
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Transfer Learning with Affine Model Transformation
Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi, Ryo Yoshida
Machine Learning
日本大学: 東京科学大学
2023 · NeurIPS
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
John Falk, Luigi Bonati, Pietro Novelli, Michele Parrinello, Massimiliano Pontil
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
Klim Kireev, Maksym Andriushchenko, Carmela Troncoso, Nicolas Flammarion
Machine Learning
日本大学: 関与なし（対象大学）
2023 · NeurIPS
Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks
Andong Wang, Chao Li, Mingyuan Bai, Zhong Jin, Guoxu Zhou, Qibin Zhao
Machine Learning
日本大学: 関与なし（対象大学）