2024 Oral Papers
315 papers found • Page 1 of 7
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks
Haruo Hosoya
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
Yuancheng Xu, Chenghao Deng, Yanchao Sun et al.
Adaptive Accompaniment with ReaLchords
Yusong Wu, Tim Cooijmans, Kyle Kastner et al.
A decoder-only foundation model for time-series forecasting
Abhimanyu Das, Weihao Kong, Rajat Sen et al.
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
Shentao Yang, Tianqi Chen, Mingyuan Zhou
A Dual-module Framework for Counterfactual Estimation over Time
Xin Wang, Shengfei Lyu, Lishan Yang et al.
A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality
Huan He, Yijie Hao, Yuanzhe Xi et al.
AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation
Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult et al.
AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang et al.
ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data
Carmen Martin-Turrero, Maxence Bouvier, Manuel Breitenstein et al.
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
Zibin Dong, Yifu Yuan, Jianye HAO et al.
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework
Eliya Segev, Maya Alroy, Ronen Katsir et al.
An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
Qiang Huang, Chuizheng Meng, Defu Cao et al.
An Emulator for Fine-tuning Large Language Models using Small Language Models
Eric Mitchell, Rafael Rafailov, Archit Sharma et al.
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Yuwei GUO, Ceyuan Yang, Anyi Rao et al.
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
Qi Zhao, Shijie Wang, Ce Zhang et al.
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
Yifei Zhou, Andrea Zanette, Jiayi Pan et al.
ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
Jiecheng Lu, Xu Han, Shihao Yang
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori, Yuhang Song, Yordan Yordanov et al.
Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks
Lihao Wang, Zhaofei Yu
AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
Qi Yan, Raihan Seraj, Jiawei He et al.
Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
Brett Daley, Martha White, Marlos C. Machado
Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures
Ganchao Wei
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
Yongsheng Mei, Mahdi Imani, Tian Lan
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
Shikai Fang, Qingsong Wen, Yingtao Luo et al.
BeigeMaps: Behavioral Eigenmaps for Reinforcement Learning from Images
Sandesh Adhikary, Anqi Li, Byron Boots
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Zichong Li, Qunzhi Xu, Zhenghao Xu et al.
Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs
Anson Simon Bastos, Kuldeep Singh, Abhishek Nadgeri et al.
Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values
Xiaodan Chen, Xiucheng Li, Bo Liu et al.
Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs
Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande et al.
Bidirectional Temporal Diffusion Model for Temporally Consistent Human Animation
Tserendorj Adiya, Jae Shin Yoon, Jung Eun Lee et al.
Boundary Denoising for Video Activity Localization
Mengmeng Xu, Mattia Soldan, Jialin Gao et al.
Brain decoding: toward real-time reconstruction of visual perception
Yohann Benchetrit, Hubert Banville, Jean-Remi King
BrainLM: A foundation model for brain activity recordings
Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Rizvi et al.
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting
xue wang, Tian Zhou, Qingsong Wen et al.
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
Guangyi Chen, Yifan Shen, Zhenhao Chen et al.
CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables
Jiecheng Lu, Xu Han, Sun et al.
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, ZHIMING ZHANG, Shu Yang
Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks
Kesen Zhao, Liang Zhang
Causal Representation Learning from Multiple Distributions: A General Setting
Kun Zhang, Shaoan Xie, Ignavier Ng et al.
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
Hiroshi Morioka, Aapo Hyvarinen
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Yulong Huang, Xiaopeng LIN, Hongwei Ren et al.
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
Yogesh Verma, Markus Heinonen, Vikas Garg
Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.
Raj Ghugare, Matthieu Geist, Glen Berseth et al.
CogBench: a large language model walks into a psychology lab
Julian Coda-Forno, Marcel Binz, Jane Wang et al.
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding
Kaiyuan Chen, Xingzhuo Guo, Yu Zhang et al.
Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
Yeda Song, Dongwook Lee, Gunhee Kim
Conditional Information Bottleneck Approach for Time Series Imputation
MinGyu Choi, Changhee Lee