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Found 9 papers, 2 papers with code
Nearest Neighbour Score Estimators for Diffusion Generative Models
Score function estimation is the cornerstone of both training and sampling from diffusion generative models.
Video Killed the HD-Map: Predicting Multi-Agent Behavior Directly From Aerial Images
The development of algorithms that learn multi-agent behavioral models using human demonstrations has led to increasingly realistic simulations in the field of autonomous driving.
Conditional Permutation Invariant Flows
We present a novel, conditional generative probabilistic model of set-valued data with a tractable log density.
Differentiable Particle Filtering without Modifying the Forward Pass
Particle filters are not compatible with automatic differentiation due to the presence of discrete resampling steps.
Robust Asymmetric Learning in POMDPs
Policies for partially observed Markov decision processes can be efficiently learned by imitating policies for the corresponding fully observed Markov decision processes.
Probabilistic Surrogate Networks for Simulators with Unbounded Randomness
Our surrogates target stochastic simulators where the number of random variables itself can be stochastic and potentially unbounded.
Amortized Rejection Sampling in Universal Probabilistic Programming
Naive approaches to amortized inference in probabilistic programs with unbounded loops can produce estimators with infinite variance.
Composing Modeling and Inference Operations with Probabilistic Program Combinators
We assume that models are dynamic, but that model composition is static, in the sense that combinator application takes place prior to evaluating the model on data.
Consistent Kernel Mean Estimation for Functions of Random Variables
We provide a theoretical foundation for non-parametric estimation of functions of random variables using kernel mean embeddings.
