Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximationby Yu Chen, Xiangcheng Zhang, Siwei Wang,…
Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planningby Tan Zhi-Xuan, Lance Ying,…
Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecastingby Daniel Iong,…
Advancing sleep detection by modelling weak label sets: A novel weakly supervised learning approachby Matthias…
A Note on Bayesian Networks with Latent Root Variablesby Marco Zaffalon, Alessandro AntonucciFirst submitted to…
Molecule Design by Latent Prompt Transformerby Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming…
On the connection between Noise-Contrastive Estimation and Contrastive Divergenceby Amanda Olmin, Jakob Lindqvist, Lennart Svensson,…
Stable Training of Normalizing Flows for High-dimensional Variational Inferenceby Daniel AndradeFirst submitted to arxiv on:…
Shaving Weights with Occam’s Razor: Bayesian Sparsification for Neural Networks Using the Marginal Likelihoodby Rayen…
Efficient semi-supervised inference for logistic regression under case-control studiesby Zhuojun Quan, Yuanyuan Lin, Kani Chen,…