Robuta

A statistical model rescues multi-mapping reads with high accuracy and demonstrates their impact in all facets of the analysis of genome-wide high throughput...

03/02/20 - Learning generative models for graph-structured data is challenging because graphs are discrete, combinatorial, and the underlying...

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Abstract page for arXiv paper 2601.05355: A Bayesian Generative Modeling Approach for Arbitrary Conditional Inference

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Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains. -...

The demand for fast magnetic field approximation for the optimal design of electromagnetic devices is urgent nowadays. However, due to the lack of a publicly...

Project description Third-cycle subject: Computer Science Cryo-EM is a method for reconstructing the 3D structure of a biological molecule using images from...

Learning generative models directly from corrupted observations is a long-standing challenge across natural and scientific domains. We introduce *Distillation...

As the world of technology continues to evolve, artificial intelligence (AI) is consistently leading the way towards innovative breakthroughs. Particularly in...

We introduce recently proposed Equivariant Descriptor Fields (EDFs), focusing on the four key model properties: generative modeling, bi-equivariance, steerable...