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The Mystery of Generalization: Why Does Deep Learning Work?
Jeffrey Pennington
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Jeffrey Pennington (Google Brain)
More from the Same Authors
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2023 Poster: Second-order regression models exhibit progressive sharpening to the edge of stability »
Atish Agarwala · Fabian Pedregosa · Jeffrey Pennington -
2022 Poster: Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm »
Lechao Xiao · Jeffrey Pennington -
2022 Poster: Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling »
Jiri Hron · Roman Novak · Jeffrey Pennington · Jascha Sohl-Dickstein -
2022 Spotlight: Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm »
Lechao Xiao · Jeffrey Pennington -
2022 Spotlight: Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling »
Jiri Hron · Roman Novak · Jeffrey Pennington · Jascha Sohl-Dickstein -
2021 Tutorial: Random Matrix Theory and ML (RMT+ML) »
Fabian Pedregosa · Courtney Paquette · Thomas Trogdon · Jeffrey Pennington -
2020 Poster: The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization »
Ben Adlam · Jeffrey Pennington -
2020 Poster: Disentangling Trainability and Generalization in Deep Neural Networks »
Lechao Xiao · Jeffrey Pennington · Samuel Schoenholz -
2019 : Poster discussion »
Roman Novak · Maxime Gabella · Frederic Dreyer · Siavash Golkar · Anh Tong · Irina Higgins · Mirco Milletari · Joe Antognini · Sebastian Goldt · Adín Ramírez Rivera · Roberto Bondesan · Ryo Karakida · Remi Tachet des Combes · Michael Mahoney · Nicholas Walker · Stanislav Fort · Samuel Smith · Rohan Ghosh · Aristide Baratin · Diego Granziol · Stephen Roberts · Dmitry Vetrov · Andrew Wilson · César Laurent · Valentin Thomas · Simon Lacoste-Julien · Dar Gilboa · Daniel Soudry · Anupam Gupta · Anirudh Goyal · Yoshua Bengio · Erich Elsen · Soham De · Stanislaw Jastrzebski · Charles H Martin · Samira Shabanian · Aaron Courville · Shorato Akaho · Lenka Zdeborova · Ethan Dyer · Maurice Weiler · Pim de Haan · Taco Cohen · Max Welling · Ping Luo · zhanglin peng · Nasim Rahaman · Loic Matthey · Danilo J. Rezende · Jaesik Choi · Kyle Cranmer · Lechao Xiao · Jaehoon Lee · Yasaman Bahri · Jeffrey Pennington · Greg Yang · Jiri Hron · Jascha Sohl-Dickstein · Guy Gur-Ari -
2019 Workshop: Theoretical Physics for Deep Learning »
Jaehoon Lee · Jeffrey Pennington · Yasaman Bahri · Max Welling · Surya Ganguli · Joan Bruna -
2019 : Opening Remarks »
Jaehoon Lee · Jeffrey Pennington · Yasaman Bahri · Max Welling · Surya Ganguli · Joan Bruna -
2018 Poster: Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks »
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz -
2018 Oral: Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks »
Minmin Chen · Jeffrey Pennington · Samuel Schoenholz -
2018 Poster: Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks »
Lechao Xiao · Yasaman Bahri · Jascha Sohl-Dickstein · Samuel Schoenholz · Jeffrey Pennington -
2018 Oral: Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks »
Lechao Xiao · Yasaman Bahri · Jascha Sohl-Dickstein · Samuel Schoenholz · Jeffrey Pennington -
2017 Poster: Geometry of Neural Network Loss Surfaces via Random Matrix Theory »
Jeffrey Pennington · Yasaman Bahri -
2017 Talk: Geometry of Neural Network Loss Surfaces via Random Matrix Theory »
Jeffrey Pennington · Yasaman Bahri