Papers
Training Private Models That Know What They Don’t Know
Stephan Rabanser, Anvith Thudi, Abhradeep Guha Thakurta et al.
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign?
Erin George, Michael Murray, William Swartworth et al.
Training Transformers with 4-bit Integers
Haocheng Xi, ChangHao Li, Jianfei Chen et al.
Training Transitive and Commutative Multimodal Transformers with LoReTTa
Manuel Tran, Yashin Dicente Cid, Amal Lahiani et al.
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function
man zhou, Naishan Zheng, Yuan Xu et al.
Train 'n Trade: Foundations of Parameter Markets
Tzu-Heng Huang, Harit Vishwakarma, Frederic Sala
Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks
Jun Yin, Chaozhuo Li, Hao Yan et al.
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
Shenzhi Wang, Qisen Yang, Jiawei Gao et al.
trajdata: A Unified Interface to Multiple Human Trajectory Datasets
Boris Ivanovic, Guanyu Song, Igor Gilitschenski et al.
Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory
Minhak Song, Chulhee Yun
Trans-Dimensional Generative Modeling via Jump Diffusion Models
Andrew Campbell, William Harvey, Christian Weilbach et al.
Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
Klim Kireev, Maksym Andriushchenko, Carmela Troncoso et al.
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
John Falk, Luigi Bonati, Pietro Novelli et al.
Transfer Learning with Affine Model Transformation
Shunya Minami, Kenji Fukumizu, Yoshihiro Hayashi et al.
Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks
Andong Wang, Chao Li, Mingyuan Bai et al.
Transformer as a hippocampal memory consolidation model based on NMDAR-inspired nonlinearity
Dong Kyum Kim, Jea Kwon, Meeyoung Cha et al.
Transformer-based Planning for Symbolic Regression
Parshin Shojaee, Kazem Meidani, Amir Barati Farimani et al.
Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars
Kaiyue Wen, Yuchen Li, Bingbin Liu et al.
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection
Yu Bai, Fan Chen, Huan Wang et al.
Transformers learn through gradual rank increase
Enric Boix-Adsera, Etai Littwin, Emmanuel Abbe et al.
Transformers learn to implement preconditioned gradient descent for in-context learning
Kwangjun Ahn, Xiang Cheng, Hadi Daneshmand et al.
Transformers over Directed Acyclic Graphs
Yuankai Luo, Veronika Thost, Lei Shi
TransHP: Image Classification with Hierarchical Prompting
Wenhao Wang, Yifan Sun, Wei Li et al.
Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction
Anagh Malik, Parsa Mirdehghan, Sotiris Nousias et al.
Transition-constant Normalization for Image Enhancement
Jie Huang, man zhou, Jinghao Zhang et al.