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2021-07
Sequential Core-Set Monte Carlo
q-Paths: Generalizing the Geometric Annealing Path using Power Means
Robust Asymmetric Learning in POMDPs
Assisting the Adversary to Improve GAN Training
2021-06
Differentiable Particle Filtering without Modifying the Forward Pass.
2021-05
Near-Optimal Glimpse Sequences for Training Hard Attention Neural Networks
Uncertainty in Neural Processes
Improving Few-Shot Visual Classification with Unlabelled Examples
2021-04
Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulation.
2021-02
Image Completion via Inference in Deep Generative Models
2020-12
Robust Asymmetric Learning in POMDPs.
Annealed Importance Sampling with q-Paths.
Ensemble Squared: A Meta AutoML System.
2020-11
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference.
2020-07
All in the (Exponential) Family: Information Geometry and Thermodynamic Variational Inference
2020-06
Semi-supervised Sequential Generative Models
Enhancing Few-Shot Image Classification with Unlabelled Examples
Improved Few-Shot Visual Classification
Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models.
Coping With Simulators That Don't Always Return.
AISTATS 2020
(2020-06-03)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:2003.12908 (2020-03-28)]2020-03
Planning as Inference in Epidemiological Models
2020-01
Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective
Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators
2019-11
Etalumis: bringing probabilistic programming to scientific simulators at scale
Etalumis: bringing probabilistic programming to scientific simulators at scale
2019-10
Attention for Inference Compilation
Deep Probabilistic Surrogate Networks for Universal Simulator Approximation
Amortized Rejection Sampling in Universal Probabilistic Programming
Efficient Bayesian Inference for Nested Simulators
Efficient Inference Amortization in Graphical Models using Structured Continuous Conditional Normalizing Flows
2019-09
Safer End-to-End Autonomous Driving via Conditional Imitation Learning and Command Augmentation
The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging.
2019-06
The Thermodynamic Variational Objective
Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training.
2019-05
Amortized Monte Carlo Integration
2019-04
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models
AISTATS 2019
(2019-04-11)
proceedings.mlr.pressPDF[Also on arXiv preprint arXiv:1903.02482 (2019-03-06)]2019-03
Imitation Learning of Factored Multi-agent Reactive Models
2019-01
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow.
2018-12
Faithful Inversion of Generative Models for Effective Amortized Inference
Bayesian Distributed Stochastic Gradient Descent
2018-09
Revisiting Reweighted Wake-Sleep
An Introduction to Probabilistic Programming
2018-07
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
On Nesting Monte Carlo Estimators
Tighter Variational Bounds are Not Necessarily Better
2018-06
Inference Trees: Adaptive Inference with Exploration
Deep Variational Reinforcement Learning for POMDPs
2018-04
Discontinuous Hamiltonian Monte Carlo for Probabilistic Programs.
Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities
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