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wellman@umich.edu.
Thursday 05 March 2020, 11:00-12:00
Engineering Department, CBL Room BE-438.
Contact: No managers listed
0 upcoming talks View 45 archived talks
Machine Learning @ CUED
Game Playing Meets Game Theory: Strategic Learning from Simulated Play
Machine Learning @ CUED
Robust Deep Learning Under Distribution Shift
Machine Learning @ CUED
Models and inference for temporal Gaussian processes
Machine Learning @ CUED
Reinforcement Learning at Huawei: Robustness, Safety, and Efficiency
Machine Learning @ CUED
Constructing temporal latent spaces: Representation learning for clustering and imputation on time series
Machine Learning @ CUED
Explaining Neural Networks: Post-hoc and Natural Language Explanations
Machine Learning @ CUED
Learning-Algorithms from Bayesian Principles
Machine Learning @ CUED
Rotation Invariant Householder Parameterization for Bayesian PCA
Machine Learning @ CUED
Two Approximate Sampling Methods for Bayesian Deep Learning
Machine Learning @ CUED
Semi-Unsupervised Learning with Deep Generative Models / Disentangling Improves VAEs' Robustness to Adversarial Attacks
Machine Learning @ CUED
Efficiency and Transferability of Neural Networks
Machine Learning @ CUED
Learning via Data Compression: Bayesian Coresets and Sparse Variational Inference
Machine Learning @ CUED
Deep Neural Networks: A Nonparametric Bayesian Approach with Local Competition
Machine Learning @ CUED
Information Consumption on Social Media: Efficiency, Trust, and Divisiveness
Machine Learning @ CUED
Why Do We Need New Hardware & Software for Machine Intelligence?
Machine Learning @ CUED
Nonparametric Generative Modeling via Optimal Transport and Diffusions with Provable Guarantees
Machine Learning @ CUED
NeVAE: A Deep Generative Model for Molecular Graphs
Machine Learning @ CUED
Global model explainability via aggregation
Machine Learning @ CUED
Robust machine learning for causal inference in health care
Machine Learning @ CUED
Online Meta-Learning
Machine Learning @ CUED
Gauge Equivariant Convolutional Networks on Manifolds
Machine Learning @ CUED
Fairness for Sequential Decision Making Algorithms
Machine Learning @ CUED
Gaussian processes for inferring latent functions in complex data models
Machine Learning @ CUED
Causal Inference for Treatment Effects: A Theory and Associated Learning Algorithms
Machine Learning @ CUED
Fast yet Simple Natural-Gradient Variational Inference in Complex Models
Machine Learning @ CUED
Variance in Policy Gradient methods and Learning Sequential Latent Variable Models
Machine Learning @ CUED
Structured deep models: Deep learning on graphs and beyond
Machine Learning @ CUED
Semi-Generative Modelling: Domain Adaptation with Cause and Effect Features
Machine Learning @ CUED
Algorithmic Glass Ceiling in Social Networks
Machine Learning @ CUED
Algorithmic Glass Ceiling in Social Networks
Machine Learning @ CUED
Variational inference for some models with Polya-Gamma latent variables and Gaussian process priors
Machine Learning @ CUED
A* Sampling
Machine Learning @ CUED
Orthologous networks in biological systems
Machine Learning @ CUED
Latent Branching Trees
Machine Learning @ CUED
Experiments with Non-parametric Topic Models
Machine Learning @ CUED
The Blended Paradigm: A Bayesian Approach to Handling Outliers and Misspecified Models
Machine Learning @ CUED
Oracle Variational Inference
Machine Learning @ CUED
Bayesian modeling for high-level real nursing activity recognition using accelerometers
β οΈ short talk
Machine Learning @ CUED
A marginal sampler for Ο-Stable Poisson-Kingman mixture models
Machine Learning @ CUED
On the Bethe approximation
Machine Learning @ CUED
Gaussian process regression on graphs
Machine Learning @ CUED
Implicit Representation Networks
Machine Learning @ CUED
Scalable Deep Gaussian Processes
Machine Learning @ CUED
Active Learning of Linear Embeddings for Gaussian Processes
Machine Learning @ CUED
Bayesian monitoring for the Comprehensive Nuclear-Test-Ban Treaty
Please see above for contact details for this list.