b'Yisong Yue'

research

∙ 07/25/2023

Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation

We study Bayesian optimization (BO) in high-dimensional and non-stationa...

0 Fengxue Zhang, et al. ∙

research

∙ 03/17/2023

Conformal Generative Modeling on Triangulated Surfaces

We propose conformal generative modeling, a framework for generative mod...

0 Victor Dorobantu, et al. ∙

research

∙ 03/03/2023

Eventual Discounting Temporal Logic Counterfactual Experience Replay

Linear temporal logic (LTL) offers a simplified way of specifying tasks ...

0 Cameron Voloshin, et al. ∙

research

∙ 12/14/2022

BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos

Quantifying motion in 3D is important for studying the behavior of human...

11 Jennifer J. Sun, et al. ∙

research

∙ 10/30/2022

FI-ODE: Certified and Robust Forward Invariance in Neural ODEs

We study how to certifiably enforce forward invariance properties in neu...

6 Yujia Huang, et al. ∙

research

∙ 10/10/2022

Neurosymbolic Programming for Science

Neurosymbolic Programming (NP) techniques have the potential to accelera...

23 Jennifer J. Sun, et al. ∙

research

∙ 08/08/2022

POLAR: Preference Optimization and Learning Algorithms for Robotics

Parameter tuning for robotic systems is a time-consuming and challenging...

0 Maegan Tucker, et al. ∙

research

∙ 07/21/2022

The MABe22 Benchmarks for Representation Learning of Multi-Agent Behavior

Real-world behavior is often shaped by complex interactions between mult...

5 Jennifer J. Sun, et al. ∙

research

∙ 07/12/2022

Compactly Restrictable Metric Policy Optimization Problems

We study policy optimization problems for deterministic Markov decision ...

13 Victor D. Dorobantu, et al. ∙

research

∙ 06/20/2022

Policy Optimization with Linear Temporal Logic Constraints

We study the problem of policy optimization (PO) with linear temporal lo...

12 Cameron Voloshin, et al. ∙

research

∙ 06/16/2022

Deep Neural Imputation: A Framework for Recovering Incomplete Brain Recordings

Neuroscientists and neuroengineers have long relied on multielectrode ne...

11 Sabera Talukder, et al. ∙

research

∙ 05/13/2022

Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds

Executing safe and precise flight maneuvers in dynamic high-speed winds ...

12 Michael O'Connell, et al. ∙

research

∙ 04/18/2022

Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies

This work presents Neural Gaits, a method for learning dynamic walking g...

0 Ivan Dario Jimenez Rodriguez, et al. ∙

research

∙ 03/22/2022

Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models

Control Barrier Functions (CBFs) have been demonstrated to be a powerful...

0 Andrew J. Taylor, et al. ∙

research

∙ 03/09/2022

MLNav: Learning to Safely Navigate on Martian Terrains

We present MLNav, a learning-enhanced path planning framework for safety...

30 Shreyansh Daftry, et al. ∙

research

∙ 03/02/2022

Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision

With the increasing prevalence of complex vision-based sensing methods f...

0 Ryan K. Cosner, et al. ∙

research

∙ 02/05/2022

LyaNet: A Lyapunov Framework for Training Neural ODEs

We propose a method for training ordinary differential equations by usin...

9 Ivan Dario Jimenez Rodriguez, et al. ∙

research

∙ 12/15/2021

Safety-Aware Preference-Based Learning for Safety-Critical Control

Bringing dynamic robots into the wild requires a tenuous balance between...

0 Ryan K. Cosner, et al. ∙

research

∙ 12/09/2021

Self-Supervised Keypoint Discovery in Behavioral Videos

We propose a method for learning the posture and structure of agents fro...

6 Jennifer J. Sun, et al. ∙

research

∙ 11/30/2021

Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis

Obtaining annotations for large training sets is expensive, especially i...

5 Albert Tseng, et al. ∙

research

∙ 10/08/2021

On the Implicit Biases of Architecture Gradient Descent

Do neural networks generalise because of bias in the functions returned ...

4 Jeremy Bernstein, et al. ∙

research

∙ 09/10/2021

Natural Multicontact Walking for Robotic Assistive Devices via Musculoskeletal Models and Hybrid Zero Dynamics

Generating provably stable walking gaits that yield natural locomotion w...

0 Kejun Li, et al. ∙

research

∙ 07/28/2021

Unsupervised Learning of Neurosymbolic Encoders

We present a framework for the unsupervised learning of neurosymbolic en...

9 Eric Zhan, et al. ∙

research

∙ 06/11/2021

Interpreting Expert Annotation Differences in Animal Behavior

Hand-annotated data can vary due to factors such as subjective differenc...

4 Megan Tjandrasuwita, et al. ∙

research

∙ 06/11/2021

Meta-Adaptive Nonlinear Control: Theory and Algorithms

We present an online multi-task learning approach for adaptive nonlinear...

14 Guanya Shi, et al. ∙

research

∙ 06/09/2021

Fine-Grained System Identification of Nonlinear Neural Circuits

We study the problem of sparse nonlinear model recovery of high dimensio...

1 Dawna Bagherian, et al. ∙

research

∙ 06/09/2021

Learning Pseudo-Backdoors for Mixed Integer Programs

We propose a machine learning approach for quickly solving Mixed Integer...

2 Aaron Ferber, et al. ∙

research

∙ 05/13/2021

End-to-End Sequential Sampling and Reconstruction for MR Imaging

Accelerated MRI shortens acquisition time by subsampling in the measurem...

19 Tianwei Yin, et al. ∙

research

∙ 04/06/2021

The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions

Multi-agent behavior modeling aims to understand the interactions that o...

2 Jennifer J. Sun, et al. ∙

research

∙ 03/08/2021

Learning Unstable Dynamics with One Minute of Data: A Differentiation-based Gaussian Process Approach

We present a straightforward and efficient way to estimate dynamics mode...

11 Ivan D. Jimenez Rodriguez, et al. ∙

research

∙ 03/02/2021

Minimax Model Learning

We present a novel off-policy loss function for learning a transition mo...

18 Cameron Voloshin, et al. ∙

research

∙ 03/01/2021

Computing the Information Content of Trained Neural Networks

How much information does a learning algorithm extract from the training...

8 Jeremy Bernstein, et al. ∙

research

∙ 02/18/2021

Learning Invariant Representation of Tasks for Robust Surgical State Estimation

Surgical state estimators in robot-assisted surgery (RAS) - especially t...

20 Yidan Qin, et al. ∙

research

∙ 01/17/2021

Disentangling Observed Causal Effects from Latent Confounders using Method of Moments

Discovering the complete set of causal relations among a group of variab...

4 Anqi Liu, et al. ∙

research

∙ 12/10/2020

Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms using Learned Interactions

We present Neural-Swarm2, a learning-based method for motion planning an...

6 Guanya Shi, et al. ∙

research

∙ 11/27/2020

Task Programming: Learning Data Efficient Behavior Representations

Specialized domain knowledge is often necessary to accurately annotate t...

17 Jennifer J. Sun, et al. ∙

research

∙ 11/21/2020

Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty

Modern nonlinear control theory seeks to endow systems with properties s...

0 Andrew J. Taylor, et al. ∙

research

∙ 11/14/2020

On the Benefits of Early Fusion in Multimodal Representation Learning

Intelligently reasoning about the world often requires integrating data ...

11 George Barnum, et al. ∙

research

∙ 11/11/2020

Machine Learning Based Path Planning for Improved Rover Navigation (Pre-Print Version)

Enhanced AutoNav (ENav), the baseline surface navigation software for NA...

10 Neil Abcouwer, et al. ∙

research

∙ 11/09/2020

ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes

Characterizing what types of exoskeleton gaits are comfortable for users...

9 Kejun Li, et al. ∙

research

∙ 11/05/2020

Architecture Agnostic Neural Networks

In this paper, we explore an alternate method for synthesizing neural ne...

19 Sabera Talukder, et al. ∙

research

∙ 10/20/2020

Iterative Amortized Policy Optimization

Policy networks are a central feature of deep reinforcement learning (RL...

12 Joseph Marino, et al. ∙

research

∙ 10/08/2020

Distributionally Robust Learning for Unsupervised Domain Adaptation

We propose a distributionally robust learning (DRL) method for unsupervi...

2 Haoxuan Wang, et al. ∙

research

∙ 07/23/2020

Learning Differentiable Programs with Admissible Neural Heuristics

We study the problem of learning differentiable functions expressed as p...

20 Ameesh Shah, et al. ∙

research

∙ 07/16/2020

Active Learning under Label Shift

Distribution shift poses a challenge for active data collection in the r...

18 Eric Zhao, et al. ∙

research

∙ 07/08/2020

Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions

We present a systematic investigation using graph neural networks (GNNs)...

10 Serim Ryou, et al. ∙

research

∙ 06/28/2020

Deep Bayesian Quadrature Policy Optimization

We study the problem of obtaining accurate policy gradient estimates. Th...

6 Akella Ravi Tej, et al. ∙

research

∙ 06/25/2020

Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries

We examine the task of locating a target region among those induced by i...

4 Akash Kumar, et al. ∙

research

∙ 06/25/2020

Learning compositional functions via multiplicative weight updates

Compositionality is a basic structural feature of both biological and ar...

35 Jeremy Bernstein, et al. ∙

research

∙ 06/18/2020

Competitive Policy Optimization

A core challenge in policy optimization in competitive Markov decision p...

16 Manish Prajapat, et al. ∙

Yisong Yue

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