248 citations · 306 across the 5 of their papers we have counts for
5 papers · 1 filter
Neural Compression of Atmospheric States
Piotr Mirowski, David Warde-Farley, Mihaela Rosca +7
Atmospheric states derived from reanalysis comprise a substantial portion of weather and climate simulation outputs. Many stakeholders -- such as researchers, policy makers, and in…
Investigating the Edge of Stability Phenomenon in Reinforcement Learning
Rares Iordan, Marc Peter Deisenroth, Mihaela Rosca
Recent progress has been made in understanding optimisation dynamics in neural networks trained with full-batch gradient descent with momentum with the uncovering of the edge of st…
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective
Florin Gogianu, Tudor Berariu, Mihaela Rosca +3
Most of the recent deep reinforcement learning advances take an RL-centric perspective and focus on refinements of the training objective. We diverge from this view and show we can…
Deep Compressed Sensing
Yan Wu, Mihaela Rosca, Timothy Lillicrap
Compressed sensing (CS) provides an elegant framework for recovering sparse signals from compressed measurements. For example, CS can exploit the structure of natural images and re…
Learning Implicit Generative Models with the Method of Learned Moments
Suman Ravuri, Shakir Mohamed, Mihaela Rosca +1
We propose a method of moments (MoM) algorithm for training large-scale implicit generative models. Moment estimation in this setting encounters two problems: it is often difficult…