Brandon Amos

16

Papers

185

Total Citations

Papers (16)

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs

Task-based End-to-end Model Learning in Stochastic Optimization

NeurIPS 2017arXiv

Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold

Wasserstein Flow Matching: Generative Modeling Over Families of Distributions

Scalable Online Planning via Reinforcement Learning Fine-Tuning

Theseus: A Library for Differentiable Nonlinear Optimization

Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world

Semi-Discrete Normalizing Flows through Differentiable Tessellation

Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information

TaskMet: Task-driven Metric Learning for Model Learning

Collapsed Variational Inference for Sum-Product Networks

OptNet: Differentiable Optimization as a Layer in Neural Networks

Input Convex Neural Networks

Depth-Limited Solving for Imperfect-Information Games

Differentiable MPC for End-to-end Planning and Control

Differentiable Convex Optimization Layers