2 papers
stat.ML2023
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou +3
Bayesian inference in deep neural networks is challenging due to the high-dimensional, strongly multi-modal parameter posterior density landscape. Markov chain Monte Carlo approach…
cs.LG2020
Investigating Efficient Learning and Compositionality in Generative LSTM Networks
Sarah Fabi, Sebastian Otte, Jonas Gregor Wiese +1
When comparing human with artificial intelligence, one major difference is apparent: Humans can generalize very broadly from sparse data sets because they are able to recombine and…