Stephan Mandt

28

Papers

217

Total Citations

Papers (28)

Exponential Family Embeddings

NeurIPS 2016arXiv

Perturbative Black Box Variational Inference

NeurIPS 2017arXiv

One Diffusion to Generate Them All

Heavy-Tailed Diffusion Models

Variational Control for Guidance in Diffusion Models

Progressive Compression with Universally Quantized Diffusion Models

Transformers for Mixed-type Event Sequences

A Complete Recipe for Diffusion Generative Models

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI

Neural NeRF Compression

Factorized Variational Autoencoders for Modeling Audience Reactions to Movies

AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data

Computationally-Efficient Neural Image Compression with Shallow Decoders

Quasi-Monte Carlo Variational Inference

Iterative Amortized Inference

Disentangled Sequential Autoencoder

Deep Generative Video Compression

Improving Inference for Neural Image Compression

User-Dependent Neural Sequence Models for Continuous-Time Event Data

Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning

Predictive Querying for Autoregressive Neural Sequence Models

Estimating the Rate-Distortion Function by Wasserstein Gradient Descent

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Zero-Shot Anomaly Detection via Batch Normalization

Lossy Image Compression with Conditional Diffusion Models

NeurIPS 2023arXiv

A Variational Analysis of Stochastic Gradient Algorithms

Dynamic Word Embeddings

Improving Optimization for Models With Continuous Symmetry Breaking