2024 Poster "variational inference" Papers
24 papers found
$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
Pierre Clavier, Tom Huix, Alain Oliviero Durmus
Accelerating Convergence in Bayesian Few-Shot Classification
Tianjun Ke, Haoqun Cao, Feng Zhou
Adaptive Robust Learning using Latent Bernoulli Variables
Aleksandr Karakulev, Dave Zachariah, Prashant Singh
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
Chengrui Li, Weihan Li, Yule Wang et al.
Amortized Variational Deep Kernel Learning
Alan Matias, César Lincoln Mattos, Joao Paulo Gomes et al.
Bayesian Exploration Networks
Mattie Fellows, Brandon Kaplowitz, Christian Schroeder de Witt et al.
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling
Denis Blessing, Xiaogang Jia, Johannes Esslinger et al.
Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution
Johannes Zenn, Robert Bamler
Discovering Mixtures of Structural Causal Models from Time Series Data
Sumanth Varambally, Yian Ma, Rose Yu
Improving Adversarial Energy-Based Model via Diffusion Process
Cong Geng, Tian Han, Peng-Tao Jiang et al.
Kernel Semi-Implicit Variational Inference
Ziheng Cheng, Longlin Yu, Tianyu Xie et al.
Online Variational Sequential Monte Carlo
Alessandro Mastrototaro, Jimmy Olsson
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
Junyi FAN, Yuxuan Han, Zijian Liu et al.
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang et al.
Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
Yunfei Long, Zilin Tian, Liguo Zhang et al.
Sample as you Infer: Predictive Coding with Langevin Dynamics
Umais Zahid, Qinghai Guo, Zafeirios Fountas
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes
Yingyi Chen, Qinghua Tao, Francesco Tonin et al.
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference
JIAN XU, Delu Zeng, John Paisley
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
Tom Huix, Anna Korba, Alain Oliviero Durmus et al.
Understanding Stochastic Natural Gradient Variational Inference
Kaiwen Wu, Jacob Gardner
Variational Inference with Coverage Guarantees in Simulation-Based Inference
Yash Patel, Declan McNamara, Jackson Loper et al.
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts
Hyunsu Kim, Ye Gon Kim, Hongseok Yang et al.
Variational Schrödinger Diffusion Models
Wei Deng, Weijian Luo, Yixin Tan et al.