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This page maintains the seminar presentations of the Bayesian Machine Learning group supervised by Dr. Shandian Zhe at the University of Utah.

Archived

How to use Sequential Monte Carlo for optimization
Date: Nov 22 2023, Presenter: Su-wei Yang
slides | video

Large Language Models Quantization (Part 2)
Date: Nov 22 2023, Presenter: Xin Yu
slides | video1 | video2

How to use Sequential Monte Carlo for optimization
Date: Nov 3 2023, Presenter: Haozhe Sun
slides

Large Language Models Quantization (Part 1)
Date: Nov 1 2023, Presenter: Xin Yu
slides | video

Recent papers in hypergraph
Date: Oct 18 2023, Presenter: Sina Rashetnia
slides | video1 | video2

A General Neural Operator Transformer for Operator Learning
Date: Sep 13 2023, Presenter: Tushar Gautam
slides | video

Kernel Integral Operator by Wavelet
Date: Sep 13 2023, Presenter: Su-Wei Yang
slides | video

HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs
Date: Sep 6 2023, Presenter: Keyan Chen
slides | video1 | video2

High-Dimensional Bayesian Optimization via Random Projection
Date: Sep 6 2023, Presenter: Zhitong Xu
slides | video

Sequential Monte-Carlo
Date: Aug 30 2023, Presenter: Haozhe Sun
slides | video

Data-driven Methods for Atomosphere Research
Date: Aug 30 2023, Presenter: Wenlin Li
slides 1 | slides 2 | video

A Continuous Analogue of the Tensor-Train Decomposition
Date: Jun 5th 2023, Presenter: Yile Li
slides

From Diffusion Model to Schrodinger Bridge
Date: Aug 31 2022, Presenter: Shikai Fang
slides | video part1 | video part2

A Deterministic Streaming Sketch for Ridge Regression
Date: Mar 18 2022, Presenter: Xin Yu
slides | video

ODE on Graph: A Diffusion Example
Date: Mar 16 2022, Presenter: Shikai Fang
slides | video

DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
Date: Mar 4 2022, Presenter: Dillon Lee
slides | video

DeepONet and Physics-Informed Operator Learning
Date: Mar 2 2022, Presenter: Shibo Li
slides | video

Scalable Gradients for Stochastic Differential Equations
Date: Feb 28 2022, Presenter: Shikai Fang
slides | video

Physics-Informed Learning of Governing Equations from Scarce Data
Date: Feb 25 2022, Presenter: Zheng Wang
slides | video

Elliptical Slice Sampling
Date: Feb 23 2022, Presenter: Da Long
slides | video

Probabilistic Network Pruning
Date: Feb 21 2022, Presenter: Xin Yu
slides | video

Dirichlet Pruning for Neural Network Compression
Date: Feb 18 2022, Presenter: Xin Yu
slides | video

Multiresolution Gaussian Processes
Date: Feb 16 2022, Presenter: Zheng Wang
slides | video

Neural Operator: Learning Maps Between Function Spaces
Date: Feb 14 2022, Presenter: Shibo Li
slides | video part1 | video part2

Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
Date: Feb 11 2022, Presenter: Nancy Lyu
slides | video

Neural Tangent Kernel and PINNs
Date: Feb 9 2022, Presenter: Madison Cooley
slides | video

Fourier Transform, Time Seriers and Point Process
Date: Nov 8 2021, Presenter: Zheng Wang
slides

Multi-Armed Bandits: An Introduction
Date: Nov 2 2021, Presenter: Shibo Li
slides

Model Selection in Bayesian Neural Networks via Horseshoe Priors
Date: Oct 26 2021, Presenter: Da Long
slides

Introduction to Kalman-Filter, SDE and LFM
Date: Oct 26 2021, Presenter: Shikai Fang
slides

Bayesian Optimization with Finite Budget
Date: Sep 14 2021, Presenter: Shibo Li
slides

Introduction to Attention
Date: Sep 14 2021, Presenter: Shikai Fang
slides

A Brief Introduction to Graph Neural Networks
Date: Sep 8 2021, Presenter: Zheng Wang
slides

Literature Review: Network Compression
Date: Sep 1 2021, Presenter: Xin Yu
slides

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