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09/14/2023
Learning to Warm-Start Fixed-Point Optimization Algorithms
We introduce a machine-learning framework to warm-start fixed-point opti...
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07/18/2023
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information
Recent works in learning-integrated optimization have shown promise in s...
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04/28/2023
Multisample Flow Matching: Straightening Flows with Minibatch Couplings
Simulation-free methods for training continuous-time generative models c...
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10/21/2022
On amortizing convex conjugates for optimal transport
This paper focuses on computing the convex conjugate operation that aris...
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10/12/2022
Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
Natural agents can effectively learn from multiple data sources that dif...
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07/19/2022
Theseus: A Library for Differentiable Nonlinear Optimization
We present Theseus, an efficient application-agnostic open source librar...
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07/11/2022
Matching Normalizing Flows and Probability Paths on Manifolds
Continuous Normalizing Flows (CNFs) are a class of generative models tha...
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06/10/2022
Meta Optimal Transport
We study the use of amortized optimization to predict optimal transport ...
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03/14/2022
Semi-Discrete Normalizing Flows through Differentiable Tessellation
Mapping between discrete and continuous distributions is a difficult tas...
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02/01/2022
Tutorial on amortized optimization for learning to optimize over continuous domains
Optimization is a ubiquitous modeling tool that is often deployed in set...
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11/23/2021
Input Convex Gradient Networks
The gradients of convex functions are expressive models of non-trivial v...
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10/07/2021
Cross-Domain Imitation Learning via Optimal Transport
Cross-domain imitation learning studies how to leverage expert demonstra...
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09/30/2021
Scalable Online Planning via Reinforcement Learning Fine-Tuning
Lookahead search has been a critical component of recent AI successes, s...
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07/21/2021
Neural Fixed-Point Acceleration for Convex Optimization
Fixed-point iterations are at the heart of numerical computing and are o...
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06/18/2021
Riemannian Convex Potential Maps
Modeling distributions on Riemannian manifolds is a crucial component in...
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05/05/2021
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints
Bridging logical and algorithmic reasoning with modern machine learning ...
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04/20/2021
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
Model-based reinforcement learning is a compelling framework for data-ef...
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11/09/2020
Neural Spatio-Temporal Point Processes
We propose a new class of parameterizations for spatio-temporal point pr...
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11/08/2020
Learning Neural Event Functions for Ordinary Differential Equations
The existing Neural ODE formulation relies on an explicit knowledge of t...
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08/28/2020
On the model-based stochastic value gradient for continuous reinforcement learning
Model-based reinforcement learning approaches add explicit domain knowle...
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06/22/2020
Aligning Time Series on Incomparable Spaces
Dynamic time warping (DTW) is a useful method for aligning, comparing an...
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02/11/2020
Objective Mismatch in Model-based Reinforcement Learning
Model-based reinforcement learning (MBRL) has been shown to be a powerfu...
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10/28/2019
Differentiable Convex Optimization Layers
Recent work has shown how to embed differentiable optimization problems ...
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10/03/2019
Generalized Inner Loop Meta-Learning
Many (but not all) approaches self-qualifying as "meta-learning" in deep...
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10/02/2019
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
Training an agent to solve control tasks directly from high-dimensional ...
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09/27/2019
The Differentiable Cross-Entropy Method
We study the Cross-Entropy Method (CEM) for the non-convex optimization ...
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06/20/2019
The Limited Multi-Label Projection Layer
We propose the Limited Multi-Label (LML) projection layer as a new primi...
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10/31/2018
Differentiable MPC for End-to-end Planning and Control
We present foundations for using Model Predictive Control (MPC) as a dif...
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05/21/2018
Depth-Limited Solving for Imperfect-Information Games
A fundamental challenge in imperfect-information games is that states do...
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04/17/2018
Learning Awareness Models
We consider the setting of an agent with a fixed body interacting with a...
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03/01/2017