Derek Nowrouzezahrai

research

∙ 09/12/2023

Efficient Graphics Representation with Differentiable Indirection

We introduce differentiable indirection – a novel learned primitive that...

0 Sayantan Datta, et al. ∙

research

∙ 05/26/2023

A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem

Training multiple agents to coordinate is an important problem with appl...

0 Paul Barde, et al. ∙

research

∙ 03/14/2023

MeshDiffusion: Score-based Generative 3D Mesh Modeling

We consider the task of generating realistic 3D shapes, which is useful ...

0 Zhen Liu, et al. ∙

research

∙ 01/12/2023

Neural Shadow Mapping

We present a neural extension of basic shadow mapping for fast, high qua...

0 Sayantan Datta, et al. ∙

research

∙ 11/02/2022

Attention-based Neural Cellular Automata

Recent extensions of Cellular Automata (CA) have incorporated key ideas ...

0 Mattie Tesfaldet, et al. ∙

research

∙ 11/01/2022

Learning Neural Implicit Representations with Surface Signal Parameterizations

Neural implicit surface representations have recently emerged as popular...

0 Yanran Guan, et al. ∙

research

∙ 10/24/2022

Learning Latent Structural Causal Models

Causal learning has long concerned itself with the accurate recovery of ...

0 Jithendaraa Subramanian, et al. ∙

research

∙ 10/03/2022

Uncertainty-Driven Active Vision for Implicit Scene Reconstruction

Multi-view implicit scene reconstruction methods have become increasingl...

0 Edward J. Smith, et al. ∙

research

∙ 07/12/2022

Latent Variable Models for Bayesian Causal Discovery

Learning predictors that do not rely on spurious correlations involves b...

0 Jithendaraa Subramanian, et al. ∙

research

∙ 03/30/2022

Challenges in leveraging GANs for few-shot data augmentation

In this paper, we explore the use of GAN-based few-shot data augmentatio...

11 Christopher Beckham, et al. ∙

research

∙ 12/14/2021

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

We are interested in interactive agents that learn to coordinate, namely...

0 Paul Barde, et al. ∙

research

∙ 08/21/2021

SSR: Semi-supervised Soft Rasterizer for single-view 2D to 3D Reconstruction

Recent work has made significant progress in learning object meshes with...

19 Issam Laradji, et al. ∙

research

∙ 08/11/2021

Dynamic Diffuse Global Illumination Resampling

Interactive global illumination remains a challenge in radiometrically- ...

0 Zander Majercik, et al. ∙

research

∙ 03/28/2021

Countering Racial Bias in Computer Graphics Research

Current computer graphics research practices contain racial biases that ...

0 Theodore Kim, et al. ∙

research

∙ 02/09/2021

Robust Motion In-betweening

In this work we present a novel, robust transition generation technique ...

12 Félix G. Harvey, et al. ∙

research

∙ 01/26/2021

Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes

Neural signed distance functions (SDFs) are emerging as an effective rep...

39 Towaki Takikawa, et al. ∙

research

∙ 11/06/2020

Affinity LCFCN: Learning to Segment Fish with Weak Supervision

Aquaculture industries rely on the availability of accurate fish body me...

16 Issam Laradji, et al. ∙

research

∙ 10/07/2020

Regularized Inverse Reinforcement Learning

Inverse Reinforcement Learning (IRL) aims to facilitate a learner's abil...

0 Wonseok Jeon, et al. ∙

research

∙ 09/17/2020

On the Effectiveness of Weight-Encoded Neural Implicit 3D Shapes

A neural implicit outputs a number indicating whether the given query po...

32 Thomas Davies, et al. ∙

research

∙ 07/04/2020

A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images

Acquiring count annotations generally requires less human effort than po...

16 Issam Laradji, et al. ∙

research

∙ 06/23/2020

Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization

Adversarial imitation learning alternates between learning a discriminat...

15 Paul Barde, et al. ∙

research

∙ 06/02/2020

Surprisal-Triggered Conditional Computation with Neural Networks

Autoregressive neural network models have been used successfully for seq...

0 Loren Lugosch, et al. ∙

research

∙ 03/23/2020

Pix2Shape – Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation

We infer and generate three-dimensional (3D) scene information from a si...

0 Sai Rajeswar, et al. ∙

research

∙ 02/24/2020

Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic

Multi-agent adversarial inverse reinforcement learning (MA-AIRL) is a re...

0 Wonseok Jeon, et al. ∙

research

∙ 11/09/2019

Robo-PlaNet: Learning to Poke in a Day

Recently, the Deep Planning Network (PlaNet) approach was introduced as ...

0 Maxime Chevalier-Boisvert, et al. ∙

research

∙ 10/29/2019

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

Millions of blind and visually-impaired (BVI) people navigate urban envi...

18 Martin Weiss, et al. ∙

research

∙ 08/06/2019

Promoting Coordination through Policy Regularization in Multi-Agent Reinforcement Learning

A central challenge in multi-agent reinforcement learning is the inducti...

0 Paul Barde, et al. ∙

research

∙ 08/08/2018

Adversarial Geometry and Lighting using a Differentiable Renderer

Many machine learning classifiers are vulnerable to adversarial attacks,...

2 Hsueh-Ti Derek Liu, et al. ∙

research

∙ 08/08/2018

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

Many machine learning image classifiers are vulnerable to adversarial at...

0 Hsueh-Ti Derek Liu, et al. ∙

Derek Nowrouzezahrai

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