Climate-Invariant Machine Learning

1 code implementation • 14 Dec 2021 • Tom Beucler, Michael Pritchard, Janni Yuval, Ankitesh Gupta, Liran Peng, Stephan Rasp, Fiaz Ahmed, Paul A. O'Gorman, J. David Neelin, Nicholas J. Lutsko, Pierre Gentine

Data-driven algorithms, in particular neural networks, can emulate the effects of unresolved processes in coarse-resolution climate models when trained on high-resolution simulation data; however, they often make large generalization errors when evaluated in conditions they were not trained on.

Lip Reading Using Convolutional Auto Encoders as Feature Extractor

no code implementations • 31 May 2018 • Dharin Parekh, Ankitesh Gupta, Shharrnam Chhatpar, Anmol Yash Kumar, Manasi Kulkarni

On BBC's LRW the proposed model performed better than the baseline model of convolutional neural networks and Long short-term memory model (Garg et al., 2016).

Classification General Classification +1