A fairly reliable trend in deep reinforcement learning is that the
perfo...
We present Manifold Diffusion Fields (MDF), an approach to learn generat...
Diffusion probabilistic models have quickly become a major approach for
...
Diffusion models (DMs) have recently emerged as SoTA tools for generativ...
We introduce GAUDI, a generative model capable of capturing the distribu...
We study the problem of novel view synthesis of a scene comprised of 3D
...
We tackle the challenge of learning a distribution over complex, realist...
State-of-the-art learning-based monocular 3D reconstruction methods lear...
Images with shared characteristics naturally form sets. For example, in ...
We propose a framework for learning neural scene representations directl...
In most machine learning training paradigms a fixed, often handcrafted, ...
Error Correcting Output Codes (ECOC) is a successful technique in multi-...
We present an application of gesture recognition using an extension of
D...