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Minimum Probability Flow Learning.
Jascha Sohl-Dickstein, Peter Battaglino, Michael Robert DeWeese: Minimum Probability Flow Learning. CoRR abs/0906.4779 (2009)
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An Unsupervised Algorithm For Learning Lie Group Transformations.
Jascha Sohl-Dickstein, Jimmy C. Wang, Bruno A. Olshausen: An Unsupervised Algorithm For Learning Lie Group Transformations. CoRR abs/1001.1027 (2010)
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Minimum Probability Flow Learning.
Jascha Sohl-Dickstein, Peter Battaglino, Michael Robert DeWeese: Minimum Probability Flow Learning. ICML 2011: 905-912
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Building a better probabilistic model of images by factorization.
Benjamin J. Culpepper, Jascha Sohl-Dickstein, Bruno A. Olshausen: Building a better probabilistic model of images by factorization. ICCV 2011: 2011-2017
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Lie Group Transformation Models for Predictive Video Coding.
Ching Ming Wang, Jascha Sohl-Dickstein, Ivana Tosic, Bruno A. Olshausen: Lie Group Transformation Models for Predictive Video Coding. DCC 2011: 83-92
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Efficient Methods for Unsupervised Learning of Probabilistic Models.
Jascha Sohl-Dickstein: Efficient Methods for Unsupervised Learning of Probabilistic Models. CoRR abs/1205.4295 (2012)
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Hamiltonian Monte Carlo with Reduced Momentum Flips.
Jascha Sohl-Dickstein: Hamiltonian Monte Carlo with Reduced Momentum Flips. CoRR abs/1205.1939 (2012)
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Hamiltonian Annealed Importance Sampling for partition function estimation.
Jascha Sohl-Dickstein, Benjamin J. Culpepper: Hamiltonian Annealed Importance Sampling for partition function estimation. CoRR abs/1205.1925 (2012)
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The Natural Gradient by Analogy to Signal Whitening, and Recipes and Tricks...
Jascha Sohl-Dickstein: The Natural Gradient by Analogy to Signal Whitening, and Recipes and Tricks for its Use. CoRR abs/1205.1828 (2012)
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Training sparse natural image models with a fast Gibbs sampler of an extended...
Lucas Theis, Jascha Sohl-Dickstein, Matthias Bethge: Training sparse natural image models with a fast Gibbs sampler of an extended state space. NIPS 2012: 1133-1141
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Efficient Methods for Unsupervised Learning of Probabilistic Models.
Jascha Sohl-Dickstein: Efficient Methods for Unsupervised Learning of Probabilistic Models. University of California, Berkeley, USA, 2012
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An adaptive low dimensional quasi-Newton sum of functions optimizer.
Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli: An adaptive low dimensional quasi-Newton sum of functions optimizer. CoRR abs/1311.2115 (2013)
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Measurably Increasing Motivation in MOOCs.
Joseph Jay Williams, Dave Paunesku, Benjamin Heley, Jascha Sohl-Dickstein: Measurably Increasing Motivation in MOOCs. AIED Workshops 2013
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Controlled experiments on millions of students to personalize learning.
Eliana Feasley, Chris Klaiber, James Irwin, Jace Kohlmeier, Jascha Sohl-Dickstein: Controlled experiments on millions of students to personalize learning. AIED Workshops 2013
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Analyzing noise in autoencoders and deep networks.
Ben Poole, Jascha Sohl-Dickstein, Surya Ganguli: Analyzing noise in autoencoders and deep networks. CoRR abs/1406.1831 (2014)
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Hamiltonian Monte Carlo Without Detailed Balance.
Jascha Sohl-Dickstein, Mayur Mudigonda, Michael Robert DeWeese: Hamiltonian Monte Carlo Without Detailed Balance. ICML 2014: 719-726
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Fast large-scale optimization by unifying stochastic gradient and...
Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli: Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods. ICML 2014: 604-612
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Modeling Higher-Order Correlations within Cortical Microcolumns.
Urs Köster, Jascha Sohl-Dickstein, Charles M. Gray, Bruno A. Olshausen: Modeling Higher-Order Correlations within Cortical Microcolumns. PLoS Comput. Biol. 10(7) (2014)
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Deep Knowledge Tracing.
Chris Piech, Jonathan Spencer, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, Jascha Sohl-Dickstein: Deep Knowledge Tracing. CoRR abs/1506.05908 (2015)
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Technical Note on Equivalence Between Recurrent Neural Network Time Series...
Jascha Sohl-Dickstein, Diederik P. Kingma: Technical Note on Equivalence Between Recurrent Neural Network Time Series Models and Variational Bayesian Models. CoRR abs/1504.08025 (2015)
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