b'Ashish Kapoor'

research

∙ 07/16/2023

Is Imitation All You Need? Generalized Decision-Making with Dual-Phase Training

We introduce DualMind, a generalist agent designed to tackle various dec...

0 Yao Wei, et al. ∙

research

∙ 03/07/2023

ConBaT: Control Barrier Transformer for Safe Policy Learning

Large-scale self-supervised models have recently revolutionized our abil...

0 Yue Meng, et al. ∙

research

∙ 01/24/2023

ClimaX: A foundation model for weather and climate

Most state-of-the-art approaches for weather and climate modeling are ba...

0 Tung Nguyen, et al. ∙

research

∙ 01/24/2023

SMART: Self-supervised Multi-task pretrAining with contRol Transformers

Self-supervised pretraining has been extensively studied in language and...

3 Yanchao Sun, et al. ∙

research

∙ 10/28/2022

Learning Modular Simulations for Homogeneous Systems

Complex systems are often decomposed into modular subsystems for enginee...

0 Jayesh K Gupta, et al. ∙

research

∙ 09/22/2022

PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training

Robotics has long been a field riddled with complex systems architecture...

7 Rogerio Bonatti, et al. ∙

research

∙ 09/22/2022

Learning to Simulate Realistic LiDARs

Simulating realistic sensors is a challenging part in data generation fo...

17 Benoit Guillard, et al. ∙

research

∙ 08/04/2022

LaTTe: Language Trajectory TransformEr

Natural language is one of the most intuitive ways to express human inte...

11 Arthur Bucker, et al. ∙

research

∙ 07/29/2022

Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions

Reinforcement Learning (RL) and continuous nonlinear control have been s...

6 Wenhao Luo, et al. ∙

research

∙ 03/25/2022

Reshaping Robot Trajectories Using Natural Language Commands: A Study of Multi-Modal Data Alignment Using Transformers

Natural language is the most intuitive medium for us to interact with ot...

0 Arthur Bucker, et al. ∙

research

∙ 03/01/2021

Representation Learning for Event-based Visuomotor Policies

Event-based cameras are dynamic vision sensors that can provide asynchro...

12 Sai Vemprala, et al. ∙

research

∙ 12/17/2020

Helping Reduce Environmental Impact of Aviation with Machine Learning

Commercial aviation is one of the biggest contributors towards climate c...

0 Ashish Kapoor, et al. ∙

research

∙ 10/30/2020

Adversarial Attacks on Optimization based Planners

Trajectory planning is a key piece in the algorithmic architecture of a ...

0 Sai Vemprala, et al. ∙

research

∙ 03/12/2020

AirSim Drone Racing Lab

Autonomous drone racing is a challenging research problem at the interse...

22 Ratnesh Madaan, et al. ∙

research

∙ 03/04/2020

Black-box Smoothing: A Provable Defense for Pretrained Classifiers

We present a method for provably defending any pretrained image classifi...

7 Hadi Salman, et al. ∙

research

∙ 01/22/2020

Safety Considerations in Deep Control Policies with Probabilistic Safety Barrier Certificates

Recent advances in Deep Machine Learning have shown promise in solving c...

0 Tom Hirshberg, et al. ∙

research

∙ 12/20/2019

Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates

Collision avoidance for multi-robot systems is a difficult challenge und...

0 Wenhao Luo, et al. ∙

research

∙ 12/04/2019

Enhancing Stratospheric Weather Analyses and Forecasts by Deploying Sensors from a Weather Balloon

The ability to analyze and forecast stratospheric weather conditions is ...

40 Kiwan Maeng, et al. ∙

research

∙ 12/01/2019

Affect-based Intrinsic Rewards for Learning General Representations

Positive affect has been linked to increased interest, curiosity and sat...

24 Dean Zadok, et al. ∙

research

∙ 09/16/2019

Learning Controls Using Cross-Modal Representations: Bridging Simulation and Reality for Drone Racing

Machines are a long way from robustly solving open-world perception-cont...

2 Rogerio Bonatti, et al. ∙

research

∙ 06/23/2019

Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting

A learned generative model often produces biased statistics relative to ...

8 Aditya Grover, et al. ∙

research

∙ 05/15/2019

Explorations and Lessons Learned in Building an Autonomous Formula SAE Car from Simulations

This paper describes the exploration and learnings during the process of...

0 Dean Zadok, et al. ∙

research

∙ 04/11/2019

Synthetic Examples Improve Generalization for Rare Classes

The ability to detect and classify rare occurrences in images has import...

18 Sara Beery, et al. ∙

research

∙ 03/25/2019

Inverse Optimal Planning for Air Traffic Control

We envision a system that concisely describes the rules of air traffic c...

0 Ekaterina Tolstaya, et al. ∙

research

∙ 09/30/2018

Identifying Bias in AI using Simulation

Machine learned models exhibit bias, often because the datasets used to ...

0 Daniel McDuff, et al. ∙

research

∙ 06/27/2018

Learn-to-Score: Efficient 3D Scene Exploration by Predicting View Utility

Camera equipped drones are nowadays being used to explore large scenes a...

0 Benjamin Hepp, et al. ∙

research

∙ 05/25/2018

Visceral Machines: Reinforcement Learning with Intrinsic Rewards that Mimic the Human Nervous System

The human autonomic nervous system has evolved over millions of years an...

2 Daniel McDuff, et al. ∙

research

∙ 02/23/2018

Verifying Controllers Against Adversarial Examples with Bayesian Optimization

Recent successes in reinforcement learning have lead to the development ...

0 Shromona Ghosh, et al. ∙

research

∙ 11/17/2017

Data-driven Planning via Imitation Learning

Robot planning is the process of selecting a sequence of actions that op...

0 Sanjiban Choudhury, et al. ∙

research

∙ 09/26/2017

Active Learning amidst Logical Knowledge

Structured prediction is ubiquitous in applications of machine learning ...

0 Emmanouil Antonios Platanios, et al. ∙

research

∙ 05/15/2017

AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

Developing and testing algorithms for autonomous vehicles in real world ...

0 Shital Shah, et al. ∙

research

∙ 11/13/2016

Learning to Gather Information via Imitation

The budgeted information gathering problem - where a robot with a fixed ...

0 Sanjiban Choudhury, et al. ∙

research

∙ 10/17/2016

Risk-Aware Algorithms for Adversarial Contextual Bandits

In this work we consider adversarial contextual bandits with risk constr...

0 Wen Sun, et al. ∙

research

∙ 02/15/2016

Quantum Perceptron Models

We demonstrate how quantum computation can provide non-trivial improveme...

0 Nathan Wiebe, et al. ∙

research

∙ 11/20/2015

Bayesian inference via rejection filtering

We provide a method for approximating Bayesian inference using rejection...

0 Nathan Wiebe, et al. ∙

research

∙ 10/25/2015

Safe Control under Uncertainty

Controller synthesis for hybrid systems that satisfy temporal specificat...

0 Dorsa Sadigh, et al. ∙

research

∙ 12/10/2014

Quantum Deep Learning

In recent years, deep learning has had a profound impact on machine lear...

0 Nathan Wiebe, et al. ∙

research

∙ 06/20/2012

On Discarding, Caching, and Recalling Samples in Active Learning

We address challenges of active learning under scarce informational reso...

0 Ashish Kapoor, et al. ∙

research

∙ 02/14/2012

Efficient Probabilistic Inference with Partial Ranking Queries

Distributions over rankings are used to model data in various settings s...

0 Jonathan Huang, et al. ∙

Ashish Kapoor

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