Disentanglement via Latent Quantization

Latent quantization imposes a strong inductive bias towards learning disentangled representations.

Vision-Based Manipulators Need to Also See from Their Hands

Instrumenting manipulators with hand-centric sensing facilitates out-of-distribution generalization.

Differentiable Annealed Importance Sampling and the Perils of Gradient Noise

Marrying Hamiltonian Monte Carlo with annealed importance sampling results in an unbiased estimate of marginal likelihood that supports pathwise derivatives. Surprisingly, stochastic gradient annealed importance sampling turns out to be inconsistent.

On the Role of Data in PAC-Bayes Bounds

State-of-the-art nonvacuous PAC-Bayes generalization bounds for neural network image classifiers.

Unsupervised Curricula for Visual Meta-Reinforcement Learning

A meta-learning agent develops an adaptive curriculum of visuomotor tasks by deep clustering its own trajectories.

Unsupervised Learning via Meta-Learning

A simple yet effective unsupervised meta-learning pipeline for image classification pre‑training.

Lazy Abstraction-Based Controller Synthesis

Efficient controller synthesis for reachability and safety specifications via on-demand abstraction construction and adaptive spatiotemporal resolution.

Lazy Abstraction-Based Control for Safety Specifications

Controller synthesis for safety specifications with on-demand abstraction construction.

Multi-Layered Abstraction-Based Controller Synthesis for Continuous-Time Systems

Controller synthesis made more efficient by introducing adaptive spatiotemporal granularity.