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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...
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03/07/2023
ConBaT: Control Barrier Transformer for Safe Policy Learning
Large-scale self-supervised models have recently revolutionized our abil...
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01/24/2023
ClimaX: A foundation model for weather and climate
Most state-of-the-art approaches for weather and climate modeling are ba...
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01/24/2023
SMART: Self-supervised Multi-task pretrAining with contRol Transformers
Self-supervised pretraining has been extensively studied in language and...
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10/28/2022
Learning Modular Simulations for Homogeneous Systems
Complex systems are often decomposed into modular subsystems for enginee...
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09/22/2022
PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training
Robotics has long been a field riddled with complex systems architecture...
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09/22/2022
Learning to Simulate Realistic LiDARs
Simulating realistic sensors is a challenging part in data generation fo...
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08/04/2022
LaTTe: Language Trajectory TransformEr
Natural language is one of the most intuitive ways to express human inte...
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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...
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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...
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03/01/2021
Representation Learning for Event-based Visuomotor Policies
Event-based cameras are dynamic vision sensors that can provide asynchro...
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12/17/2020
Helping Reduce Environmental Impact of Aviation with Machine Learning
Commercial aviation is one of the biggest contributors towards climate c...
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10/30/2020
Adversarial Attacks on Optimization based Planners
Trajectory planning is a key piece in the algorithmic architecture of a ...
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03/12/2020
AirSim Drone Racing Lab
Autonomous drone racing is a challenging research problem at the interse...
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03/04/2020
Black-box Smoothing: A Provable Defense for Pretrained Classifiers
We present a method for provably defending any pretrained image classifi...
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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...
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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...
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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 ...
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12/01/2019
Affect-based Intrinsic Rewards for Learning General Representations
Positive affect has been linked to increased interest, curiosity and sat...
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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...
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06/23/2019
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
A learned generative model often produces biased statistics relative to ...
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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...
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04/11/2019
Synthetic Examples Improve Generalization for Rare Classes
The ability to detect and classify rare occurrences in images has import...
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03/25/2019
Inverse Optimal Planning for Air Traffic Control
We envision a system that concisely describes the rules of air traffic c...
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09/30/2018
Identifying Bias in AI using Simulation
Machine learned models exhibit bias, often because the datasets used to ...
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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...
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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...
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02/23/2018
Verifying Controllers Against Adversarial Examples with Bayesian Optimization
Recent successes in reinforcement learning have lead to the development ...
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11/17/2017
Data-driven Planning via Imitation Learning
Robot planning is the process of selecting a sequence of actions that op...
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09/26/2017
Active Learning amidst Logical Knowledge
Structured prediction is ubiquitous in applications of machine learning ...
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05/15/2017
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
Developing and testing algorithms for autonomous vehicles in real world ...
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11/13/2016
Learning to Gather Information via Imitation
The budgeted information gathering problem - where a robot with a fixed ...
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10/17/2016
Risk-Aware Algorithms for Adversarial Contextual Bandits
In this work we consider adversarial contextual bandits with risk constr...
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02/15/2016
Quantum Perceptron Models
We demonstrate how quantum computation can provide non-trivial improveme...
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11/20/2015
Bayesian inference via rejection filtering
We provide a method for approximating Bayesian inference using rejection...
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10/25/2015
Safe Control under Uncertainty
Controller synthesis for hybrid systems that satisfy temporal specificat...
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12/10/2014
Quantum Deep Learning
In recent years, deep learning has had a profound impact on machine lear...
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06/20/2012
On Discarding, Caching, and Recalling Samples in Active Learning
We address challenges of active learning under scarce informational reso...
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02/14/2012