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Poster spotlights
Roman Novak · Frederic Dreyer · Siavash Golkar · Irina Higgins · Joe Antognini · Ryo Karakida · Rohan Ghosh

Fri Jun 14 09:40 AM -- 10:20 AM (PDT) @

A Quantum Field Theory of Representation Learning Robert Bamler (University of California at Irvine)*; Stephan Mandt (University of California, Irivine)

Covariance in Physics and Convolutional Neural Networks Miranda Cheng (University of Amsterdam)*; Vassilis Anagiannis (University of Amsterdam); Maurice Weiler (University of Amsterdam); Pim de Haan (University of Amsterdam); Taco S. Cohen (Qualcomm AI Research); Max Welling (University of Amsterdam)

Scale Steerable Filters for Locally Scale-Invariant Convolutional Neural Networks Rohan Ghosh (National University of Singapore)*; Anupam Gupta (National University of Singapore)

Towards a Definition of Disentangled Representations Irina Higgins (DeepMind)*; David Amos (DeepMind); Sebastien Racaniere (DeepMind); David Pfau (); Loic Matthey (DeepMind); Danilo Jimenez Rezende (Google DeepMind)

Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes Roman Novak (Google Brain)*; Lechao Xiao (Google Brain); Jaehoon Lee (Google Brain); Yasaman Bahri (Google Brain); Greg Yang (Microsoft Research AI); Jiri Hron (University of Cambridge); Daniel Abolafia (Google Brain); Jeffrey Pennington (Google Brain); Jascha Sohl-Dickstein (Google Brain)

Finite size corrections for neural network Gaussian processes Joseph M Antognini (Whisper AI)*

Pathological Spectrum of the Fisher Information Matrix in Deep Neural Networks Ryo Karakida (National Institute of Advanced Industrial Science and Technology)*; Shotaro Akaho (AIST); Shun-ichi Amari (RIKEN)

Inferring the quantum density matrix with machine learning Kyle Cranmer (New York University); Siavash Golkar (NYU)*; Duccio Pappadopulo (Bloomberg)

Jet grooming through reinforcement learning Frederic Dreyer (University of Oxford)*; Stefano Carrazza (University of Milan)

Author Information

Roman Novak (Google Brain)
Frederic Dreyer (University of Oxford)

Theoretical physics researcher working on quantum chromodynamics and applications of machine learning for the LHC.

Siavash Golkar (New York University)
Irina Higgins (DeepMind)
Irina Higgins

Irina Higgins is a research scientist at DeepMind, where she works in the Froniers team. Her work aims to bring together insights from the fields of neuroscience and physics to advance general artificial intelligence through improved representation learning. Before joining DeepMind, Irina was a British Psychological Society Undergraduate Award winner for her achievements as an undergraduate student in Experimental Psychology at Westminster University, followed by a DPhil at the Oxford Centre for Computational Neuroscience and Artificial Intelligence, where she focused on understanding the computational principles underlying speech processing in the auditory brain. During her DPhil, Irina also worked on developing poker AI, applying machine learning in the finance sector, and working on speech recognition at Google Research.

Joe Antognini (Whisper AI)
Ryo Karakida (National Institute of AIST)
Rohan Ghosh (National University of Singapore)

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