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09/01/2023
Suicidal Pedestrian: Generation of Safety-Critical Scenarios for Autonomous Vehicles
Developing reliable autonomous driving algorithms poses challenges in te...
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05/22/2023
Improved Compositional Generalization by Generating Demonstrations for Meta-Learning
Meta-learning and few-shot prompting are viable methods to induce certai...
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01/30/2023
Hierarchical Imitation Learning with Vector Quantized Models
The ability to plan actions on multiple levels of abstraction enables in...
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10/25/2022
Learning Explicit Object-Centric Representations with Vision Transformers
With the recent successful adaptation of transformers to the vision doma...
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10/25/2022
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
Offline reinforcement learning, by learning from a fixed dataset, makes ...
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10/04/2022
Continuous Monte Carlo Graph Search
In many complex sequential decision making tasks, online planning is cru...
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07/06/2022
Compositional Generalization in Grounded Language Learning via Induced Model Sparsity
We provide a study of how induced model sparsity can help achieve compos...
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04/11/2022
Improved Training of Physics-Informed Neural Networks with Model Ensembles
Learning the solution of partial differential equations (PDEs) with a ne...
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04/11/2022
Learning Trajectories of Hamiltonian Systems with Neural Networks
Modeling of conservative systems with neural networks is an area of acti...
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11/08/2021
A Relational Model for One-Shot Classification
We show that a deep learning model with built-in relational inductive bi...
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10/04/2021
Automating Privilege Escalation with Deep Reinforcement Learning
AI-based defensive solutions are necessary to defend networks and inform...
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10/04/2021
Learning to Assist Agents by Observing Them
The ability of an AI agent to assist other agents, such as humans, is an...
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10/04/2021
Behaviour-conditioned policies for cooperative reinforcement learning tasks
The cooperation among AI systems, and between AI systems and humans is b...
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08/31/2021
Medical SANSformers: Training self-supervised transformers without attention for Electronic Medical Records
We leverage deep sequential models to tackle the problem of predicting h...
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06/15/2021
End-to-End Learning of Keypoint Representations for Continuous Control from Images
In many control problems that include vision, optimal controls can be in...
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12/22/2020
Learning to Play Imperfect-Information Games by Imitating an Oracle Planner
We consider learning to play multiplayer imperfect-information games wit...
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04/28/2020
Conditional Spoken Digit Generation with StyleGAN
This paper adapts a StyleGAN model for speech generation with minimal or...
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10/12/2019
Regularizing Model-Based Planning with Energy-Based Models
Model-based reinforcement learning could enable sample-efficient learnin...
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03/28/2019
Regularizing Trajectory Optimization with Denoising Autoencoders
Trajectory optimization with learned dynamics models can often suffer fr...
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11/29/2017
Semi-Supervised Few-Shot Learning with Prototypical Networks
We consider the problem of semi-supervised few-shot classification (when...
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07/28/2017
Recurrent Ladder Networks
We propose a recurrent extension of the Ladder networks whose structure ...
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10/02/2014