Bayesian Flow Networks
PulseAugur coverage of Bayesian Flow Networks — every cluster mentioning Bayesian Flow Networks across labs, papers, and developer communities, ranked by signal.
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Bayesian Flow Networks unify discrete and continuous offline RL
Researchers have introduced Bayesian Flow Networks (BFNs) as a unified framework for offline reinforcement learning (RL) and trajectory planning. This new approach, termed BFN-RL, can natively handle both discrete and c…
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New Bayesian Sample Inference model improves generative modeling
Researchers have introduced Bayesian Sample Inference (BSI), a novel generative modeling approach that views diffusion-like processes through the lens of iterative Gaussian posterior inference. This formulation treats t…
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New Fused Bayesian Flow Network for Dual-Target Molecular Design
Researchers have introduced FusedBFN, a novel Bayesian flow network designed for dual-target molecular design. This approach aims to generate molecules that can simultaneously interact with two protein targets, a key st…
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AMix-1 protein model uses Bayesian Flow Networks for enhanced design
Researchers have developed AMix-1, a protein foundation model utilizing Bayesian Flow Networks and a novel training methodology. This model demonstrates scalable pretraining, emergent capabilities, and effective in-cont…