Oral Papers
1,594 papers found • Page 32 of 32
Conference
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks
Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi et al.
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
Fengdi Che, Chenjun Xiao, Jincheng Mei et al.
Taylor Videos for Action Recognition
Lei Wang, Xiuyuan Yuan, Tom Gedeon et al.
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
Defu Cao, Furong Jia, Sercan Arik et al.
Temporal Generalization Estimation in Evolving Graphs
Bin Lu, Tingyan Ma, Xiaoying Gan et al.
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
Zijian Guo, Weichao Zhou, Wenchao Li
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning
Mingqing Xiao, Yixin Zhu, Di He et al.
TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts
Hyunwook Lee, Sungahn Ko
The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.
Aaron Spieler, Nasim Rahaman, Georg Martius et al.
The Generalization Gap in Offline Reinforcement Learning
Ishita Mediratta, Qingfei You, Minqi Jiang et al.
Threaten Spiking Neural Networks through Combining Rate and Temporal Information
Zecheng Hao, Tong Bu, Xinyu Shi et al.
TiC-CLIP: Continual Training of CLIP Models
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari et al.
TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
Xiwen Chen, Peijie Qiu, Wenhui Zhu et al.
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
Shiyu Wang, Haixu Wu, Xiaoming Shi et al.
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong et al.
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
Jiaxiang Dong, Haixu Wu, Yuxuan Wang et al.
Towards Principled Representation Learning from Videos for Reinforcement Learning
Dipendra Kumar Misra, Akanksha Saran, Tengyang Xie et al.
Towards Understanding Factual Knowledge of Large Language Models
Xuming Hu, Junzhe Chen, Xiaochuan Li et al.
Translation Equivariant Transformer Neural Processes
Matthew Ashman, Cristiana Diaconu, Junhyuck Kim et al.
T-Rep: Representation Learning for Time Series using Time-Embeddings
Archibald Fraikin, Adrien Bennetot, Stephanie Allassonniere
TSLANet: Rethinking Transformers for Time Series Representation Learning
Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen et al.
UC-NERF: Neural Radiance Field for Under-Calibrated Multi-View Cameras in Autonomous Driving
Kai Cheng, Xiaoxiao Long, Wei Yin et al.
Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training
Jinxia Yang, Bing Su, Xin Zhao et al.
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation
Devavrat Tomar, Guillaume Vray, Jean-Philippe Thiran et al.
Unsupervised Representation Learning of Brain Activity via Bridging Voxel Activity and Functional Connectivity
Ali Behrouz, Parsa Delavari, Farnoosh Hashemi
Unveiling Options with Neural Network Decomposition
Mahdi Alikhasi, Levi Lelis
UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
Yunhao Zhang, Liu Minghao, Shengyang Zhou et al.
Using AI Uncertainty Quantification to Improve Human Decision-Making
Laura Marusich, Jonathan Bakdash, Yan Zhou et al.
Value-Evolutionary-Based Reinforcement Learning
Pengyi Li, Jianye Hao, Hongyao Tang et al.
VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition
Chenyu Liu, XINLIANG ZHOU, Zhengri Zhu et al.
VDT: General-purpose Video Diffusion Transformers via Mask Modeling
Haoyu Lu, Guoxing Yang, Nanyi Fei et al.
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp et al.
VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation
Jinxi Xiang, Ricong Huang, Jun Zhang et al.
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
Yang Jin, Zhicheng Sun, Kun Xu et al.
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
Hao Fei, Shengqiong Wu, Wei Ji et al.
video-SALMONN: Speech-Enhanced Audio-Visual Large Language Models
Guangzhi Sun, Wenyi Yu, Changli Tang et al.
ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models
İlker Kesen, Andrea Pedrotti, Mustafa Dogan et al.
Visual Representation Learning with Stochastic Frame Prediction
Huiwon Jang, Dongyoung Kim, Junsu Kim et al.
VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE
Haonan Yu, Wei Xu
What Matters to You? Towards Visual Representation Alignment for Robot Learning
Thomas Tian, Chenfeng Xu, Masayoshi Tomizuka et al.
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
Zhening Li, Gabriel Poesia, Armando Solar-Lezama
WildChat: 1M ChatGPT Interaction Logs in the Wild
Wenting Zhao, Xiang Ren, Jack Hessel et al.
Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML
Robin van de Water, Hendrik Schmidt, Paul Elbers et al.
ZeroFlow: Scalable Scene Flow via Distillation
Kyle Vedder, Neehar Peri, Nathaniel Chodosh et al.