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Poster
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Fri 16:30
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Deep Learning for Computing Convergence Rates of Markov Chains
Yanlin Qu · Jose Blanchet · Peter W Glynn
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Poster
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Wed 11:00
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Solving Zero-Sum Markov Games with Continuous State via Spectral Dynamic Embedding
Chenhao Zhou · Zebang Shen · zhang chao · Hanbin Zhao · Hui Qian
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Workshop
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MHP-DDP: Multivariate Hawkes Process with Dependent Dirichlet Process
Alex Jiang · Abel Rodriguez
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Workshop
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Transformers Learn to Compress Variable-order Markov Chains in-Context
Ruida Zhou · Chao Tian · Suhas Diggavi
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Workshop
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TP2DP2: A Bayesian Mixture Model of Temporal Point Processes with Determinantal Point Process Prior
Yiwei Dong · Shaoxin Ye · Yuwen Cao · Qiyu Han · Hongteng Xu · Hanfang Yang
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Poster
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Wed 11:00
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Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment
Jiawei Chen · 春晖 赵
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Workshop
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Controlling Forgetting with Test-Time Data in Continual Learning
Vaibhav Singh · Rahaf Aljundi · Eugene Belilovsky
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Workshop
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Unsupervised Event Outlier Detection in Continuous Time
Somjit Nath · Kry Yik Chau Lui · Siqi Liu
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Workshop
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Sun 11:20
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The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
Ezra Edelman · Nikolaos Tsilivis · Surbhi Goel · Benjamin Edelman · Eran Malach
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Workshop
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Uncovering the Risk of Model Collapsing in Self-Supervised Continual Test-time Adaptation
Trung Hieu Hoang · MinhDuc Vo · Minh Do
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Poster
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Wed 11:00
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3D Gaussian Splatting as Markov Chain Monte Carlo
Shakiba Kheradmand · Daniel Rebain · Gopal Sharma · Weiwei Sun · Yang-Che Tseng · Hossam Isack · Abhishek Kar · Andrea Tagliasacchi · Kwang Moo Yi
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Poster
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Fri 16:30
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The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
Ezra Edelman · Nikolaos Tsilivis · Benjamin Edelman · Eran Malach · Surbhi Goel
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