• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 52 matches

• 2022
• 
  Sean Mann, Eric Fadel, Samuel S. Schoenholz, Ekin D. Cubuk, Steven G. Johnson, Giuseppe Romano:
  ∂PV: An end-to-end differentiable solar-cell simulator. Comput. Phys. Commun. 272: 108232 (2022)
• 
  Atish Agarwala, Samuel S. Schoenholz:
  Deep equilibrium networks are sensitive to initialization statistics. ICML 2022: 136-160
• 
  Roman Novak, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  Fast Finite Width Neural Tangent Kernel. ICML 2022: 17018-17044
• 
  Roman Novak, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  Fast Finite Width Neural Tangent Kernel. CoRR abs/2206.08720 (2022)
• 
  Atish Agarwala, Samuel S. Schoenholz:
  Deep equilibrium networks are sensitive to initialization statistics. CoRR abs/2207.09432 (2022)
• 
  Stanislav Fort, Ekin Dogus Cubuk, Surya Ganguli, Samuel S. Schoenholz:
  What does a deep neural network confidently perceive? The effective dimension of high certainty class manifolds and their low confidence boundaries. CoRR abs/2210.05546 (2022)
• 2021
• 
  Amil Merchant, Luke Metz, Samuel S. Schoenholz, Ekin D. Cubuk:
  Learn2Hop: Learned Optimization on Rough Landscapes. ICML 2021: 7643-7653
• 
  Miguel Ruiz-Garcia, Ge Zhang, Samuel S. Schoenholz, Andrea J. Liu:
  Tilting the playing field: Dynamical loss functions for machine learning. ICML 2021: 9157-9167
• 
  Neha S. Wadia, Daniel Duckworth, Samuel S. Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein:
  Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization. ICML 2021: 10617-10629
• 
  Miguel Ruiz-Garcia, Ge Zhang, Samuel S. Schoenholz, Andrea J. Liu:
  Tilting the playing field: Dynamical loss functions for machine learning. CoRR abs/2102.03793 (2021)
• 
  Amil Merchant, Luke Metz, Samuel S. Schoenholz, Ekin Dogus Cubuk:
  Learn2Hop: Learned Optimization on Rough Landscapes. CoRR abs/2107.09661 (2021)
• 
  James Martens, Andy Ballard, Guillaume Desjardins, Grzegorz Swirszcz, Valentin Dalibard, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping. CoRR abs/2110.01765 (2021)
• 
  Luke Metz, C. Daniel Freeman, Samuel S. Schoenholz, Tal Kachman:
  Gradients are Not All You Need. CoRR abs/2111.05803 (2021)
• 2020
• 
  Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  Neural Tangents: Fast and Easy Infinite Neural Networks in Python. ICLR 2020
• 
  Lechao Xiao, Jeffrey Pennington, Samuel Schoenholz:
  Disentangling Trainability and Generalization in Deep Neural Networks. ICML 2020: 10462-10472
• 
  Jaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington, Ben Adlam, Lechao Xiao, Roman Novak, Jascha Sohl-Dickstein:
  Finite Versus Infinite Neural Networks: an Empirical Study. NeurIPS 2020
• 
  Samuel S. Schoenholz, Ekin Dogus Cubuk:
  JAX MD: A Framework for Differentiable Physics. NeurIPS 2020
• 
  Jascha Sohl-Dickstein, Roman Novak, Samuel S. Schoenholz, Jaehoon Lee:
  On the infinite width limit of neural networks with a standard parameterization. CoRR abs/2001.07301 (2020)
• 
  Jaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington, Ben Adlam, Lechao Xiao, Roman Novak, Jascha Sohl-Dickstein:
  Finite Versus Infinite Neural Networks: an Empirical Study. CoRR abs/2007.15801 (2020)
• 
  Neha S. Wadia, Daniel Duckworth, Samuel S. Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein:
  Whitening and second order optimization both destroy information about the dataset, and can make generalization impossible. CoRR abs/2008.07545 (2020)
• 
  Atish Agarwala, Jeffrey Pennington, Yann N. Dauphin, Samuel S. Schoenholz:
  Temperature check: theory and practice for training models with softmax-cross-entropy losses. CoRR abs/2010.07344 (2020)
• 2019
• 
  Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  A Mean Field Theory of Batch Normalization. ICLR (Poster) 2019
• 
  Yann N. Dauphin, Samuel S. Schoenholz:
  MetaInit: Initializing learning by learning to initialize. NeurIPS 2019: 12624-12636
• 
  Jaehoon Lee, Lechao Xiao, Samuel S. Schoenholz, Yasaman Bahri, Roman Novak, Jascha Sohl-Dickstein, Jeffrey Pennington:
  Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent. NeurIPS 2019: 8570-8581
• 
  Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington:
  Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. CoRR abs/1901.08987 (2019)
• 
  Jaehoon Lee, Lechao Xiao, Samuel S. Schoenholz, Yasaman Bahri, Jascha Sohl-Dickstein, Jeffrey Pennington:
  Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent. CoRR abs/1902.06720 (2019)
• 
  Greg Yang, Jeffrey Pennington, Vinay Rao, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  A Mean Field Theory of Batch Normalization. CoRR abs/1902.08129 (2019)
• 
  Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  Neural Tangents: Fast and Easy Infinite Neural Networks in Python. CoRR abs/1912.02803 (2019)
• 
  Lechao Xiao, Jeffrey Pennington, Samuel S. Schoenholz:
  Disentangling trainability and generalization in deep learning. CoRR abs/1912.13053 (2019)
• 2018
• 
  Jeffrey Pennington, Samuel S. Schoenholz, Surya Ganguli:
  The emergence of spectral universality in deep networks. AISTATS 2018: 1924-1932

skipping 22 more matches