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06/09/2023
Value function estimation using conditional diffusion models for control
A fairly reliable trend in deep reinforcement learning is that the perfo...
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05/24/2023
Manifold Diffusion Fields
We present Manifold Diffusion Fields (MDF), an approach to learn generat...
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03/01/2023
Diffusion Probabilistic Fields
Diffusion probabilistic models have quickly become a major approach for ...
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10/10/2022
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
Diffusion models (DMs) have recently emerged as SoTA tools for generativ...
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07/27/2022
GAUDI: A Neural Architect for Immersive 3D Scene Generation
We introduce GAUDI, a generative model capable of capturing the distribu...
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07/12/2021
Fast and Explicit Neural View Synthesis
We study the problem of novel view synthesis of a scene comprised of 3D ...
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04/01/2021
Unconstrained Scene Generation with Locally Conditioned Radiance Fields
We tackle the challenge of learning a distribution over complex, realist...
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06/27/2020
On the generalization of learning-based 3D reconstruction
State-of-the-art learning-based monocular 3D reconstruction methods lear...
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06/18/2020
Set Distribution Networks: a Generative Model for Sets of Images
Images with shared characteristics naturally form sets. For example, in ...
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06/13/2020
Equivariant Neural Rendering
We propose a framework for learning neural scene representations directl...
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05/15/2019
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
In most machine learning training paradigms a fixed, often handcrafted, ...
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02/27/2015
Error-Correcting Factorization
Error Correcting Output Codes (ECOC) is a successful technique in multi-...
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10/16/2014
