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Derek Nowrouzezahrai

13 accepted papers

2025

STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent

Yewon Lee, Andrew Zou Li, Philip Huang, Eric Heiden, Krishna Murthy Jatavallabhula, Fabian Damken +4
RA-L 2025

Planning for sequential robotics tasks often requires integrated symbolic and geometric reasoning. TAMP algorithms typically solve these problems by performing a tree search over high-level task sequences while checking for kinematic and dynamic feasibility. This can be inefficient because, typicall

Cited by 8Source ↗Scholar ↗
2023

MeshDiffusion: Score-based Generative 3D Mesh Modeling

Zhen Liu, Yao Feng, Michael J. Black, Derek Nowrouzezahrai, Liam Paull, Weiyang Liu
ICLR 2023top-25%

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are more desirable in practice, because (1) they enable easy and…

Cited by 175Source ↗PDF ↗code ↗Scholar ↗
2022

Kubric: A Scalable Dataset Generator

Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth +28
CVPR 2022poster

Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and training details. But collecting, processing and annotating real data at scale is difficult, expensive, and frequently raises a…

Cited by 249PDF ↗code ↗Scholar ↗
2022

Learning to Guide and to be Guided in the Architect-Builder Problem

Paul Barde, Tristan Karch, Derek Nowrouzezahrai, Clément Moulin-Frier, Christopher Pal, Pierre-Yves Oudeyer
ICLR 2022poster

We are interested in interactive agents that learn to coordinate, namely, a $builder$ -- which performs actions but ignores the goal of the task, i.e. has no access to rewards -- and an $architect$ which guides the builder towards the goal of the task. We define and explore a formal setting where a…

Cited by 6Source ↗PDF ↗code ↗Scholar ↗
2021

Neural Geometric Level of Detail: Real-Time Rendering With Implicit 3D Shapes

Towaki Takikawa, Joey Litalien, Kangxue Yin, Karsten Kreis, Charles Loop, Derek Nowrouzezahrai +3
CVPR 2021poster

Neural signed distance functions (SDFs) are emerging as an effective representation for 3D shapes. State-of-the-art methods typically encode the SDF with a large, fixed-size neural network to approximate complex shapes with implicit surfaces. Rendering with these large networks is, however, computat…

Cited by 543PDF ↗code ↗Scholar ↗
2021

Regularized Inverse Reinforcement Learning

Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau
ICLR 2021spotlight

Inverse Reinforcement Learning (IRL) aims to facilitate a learner’s ability to imitate expert behavior by acquiring reward functions that explain the expert’s decisions. Regularized IRLapplies strongly convex regularizers to the learner’s policy in order to avoid the expert’s behavior being rational…

Cited by 15Source ↗PDF ↗Scholar ↗
2021

gradSim: Differentiable simulation for system identification and visuomotor control

J. Krishna Murthy, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss +8
ICLR 2021poster

In this paper, we tackle the problem of estimating object physical properties such as mass, friction, and elasticity directly from video sequences. Such a system identification problem is fundamentally ill-posed due to the loss of information during image formation. Current best solutions to the pro…

Cited by 40Source ↗PDF ↗Scholar ↗
2020

Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization

Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Chris Pal, Derek Nowrouzezahrai
NeurIPS 2020spotlight

Adversarial Imitation Learning alternates between learning a discriminator -- which tells apart expert's demonstrations from generated ones -- and a generator's policy to produce trajectories that can fool this discriminator. This alternated optimization is known to be delicate in practice since it…

Cited by 33Source ↗PDF ↗code ↗Scholar ↗
2020

Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning

Julien Roy, Paul Barde, Félix Harvey, Derek Nowrouzezahrai, Chris Pal
NeurIPS 2020poster

In multi-agent reinforcement learning, discovering successful collective behaviors is challenging as it requires exploring a joint action space that grows exponentially with the number of agents. While the tractability of independent agent-wise exploration is appealing, this approach fails on tasks…

Cited by 31Source ↗PDF ↗Scholar ↗
2020

Using Speech Synthesis to Train End-To-End Spoken Language Understanding Models

Loren Lugosch, Brett H. Meyer, Derek Nowrouzezahrai, Mirco Ravanelli
ICASSP 2020accepted

End-to-end models are an attractive new approach to spoken language understanding (SLU) in which the meaning of an utterance is inferred directly from the raw audio, without employing the standard pipeline composed of a separately trained speech recognizer and natural language understanding module.…

Cited by 0Source ↗Scholar ↗
2019

Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer

Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson
ICLR 2019poster

Many machine learning image classifiers are vulnerable to adversarial attacks, inputs with perturbations designed to intentionally trigger misclassification. Current adversarial methods directly alter pixel colors and evaluate against pixel norm-balls: pixel perturbations smaller than a specified ma…

Cited by 120Source ↗PDF ↗Scholar ↗
2019

Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments

Martin Weiss, Simon Chamorro, Roger Girgis, Margaux Luck, Samira E. Kahou, Joseph P. Cohen +4
CoRL 2019

Millions of blind and visually-impaired (BVI) people navigate urban environments everyday, using smartphones for high-level path-planning and white canes or guide dogs for local information. However, many BVI people still struggle to travel to new places. In our endeavour to create a navigation assi

Cited by 0Source ↗PDF ↗code ↗Scholar ↗