David Rügamer
@davidruegamer.bsky.social
Associate Prof @ LMU Munich
PI @ Munich Center for Machine Learning
Ellis Member
Associate Fellow @ relAI
-----
https://davidruegamer.github.io/ | https://www.muniq.ai/
-----
BNNs, UQ in DL, DL Theory (Overparam, Implicit Bias, Optim), Sparsity
PI @ Munich Center for Machine Learning
Ellis Member
Associate Fellow @ relAI
-----
https://davidruegamer.github.io/ | https://www.muniq.ai/
-----
BNNs, UQ in DL, DL Theory (Overparam, Implicit Bias, Optim), Sparsity
Interested in blazingly fast (10x faster than previous methods), effectively tuning-free, high-performance sampling-based inference for Bayesian Neural Networks?
Then check out our ICLR 2025 paper on Microcanonical Langevin Ensembles (MILE)! 🔥
openreview.net/pdf?id=QMtrW...
Then check out our ICLR 2025 paper on Microcanonical Langevin Ensembles (MILE)! 🔥
openreview.net/pdf?id=QMtrW...
February 10, 2025 at 11:58 AM
Interested in blazingly fast (10x faster than previous methods), effectively tuning-free, high-performance sampling-based inference for Bayesian Neural Networks?
Then check out our ICLR 2025 paper on Microcanonical Langevin Ensembles (MILE)! 🔥
openreview.net/pdf?id=QMtrW...
Then check out our ICLR 2025 paper on Microcanonical Langevin Ensembles (MILE)! 🔥
openreview.net/pdf?id=QMtrW...