More from the Same Authors

• 2022 : Investigating Reproducibility from the Decision Boundary Perspective. »
  Gowthami Somepalli · Arpit Bansal · Liam Fowl · Ping-yeh Chiang · Yehuda Dar · Richard Baraniuk · Micah Goldblum · Tom Goldstein
• 2022 : Retrieval-based Controllable Molecule Generation »
  Jack Wang · Weili Nie · Zhuoran Qiao · Chaowei Xiao · Richard Baraniuk · Anima Anandkumar
• 2022 : Exact Visualization of Deep Neural Network Geometry and Decision Boundary »
  Ahmed Imtiaz Humayun · Randall Balestriero · Richard Baraniuk
• 2022 : Using Deep Learning and Macroscopic Imaging of Porcine Heart Valve Leaflets to Predict Uniaxial Stress-Strain Responses »
  Luis Victor · CJ Barberan · Richard Baraniuk · Jane Grande-Allen
• 2022 Poster: Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference »
  Jasper Tan · Blake Mason · Hamid Javadi · Richard Baraniuk
• 2021 Poster: The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization »
  Daniel LeJeune · Hamid Javadi · Richard Baraniuk
• 2020 : Opening Remarks »
  Reinhard Heckel · Paul Hand · Soheil Feizi · Lenka Zdeborová · Richard Baraniuk
• 2020 Workshop: Workshop on Deep Learning and Inverse Problems »
  Reinhard Heckel · Paul Hand · Richard Baraniuk · Lenka Zdeborová · Soheil Feizi
• 2020 Poster: Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks »
  Randall Balestriero · Sebastien PARIS · Richard Baraniuk
• 2020 Poster: MomentumRNN: Integrating Momentum into Recurrent Neural Networks »
  Tan Nguyen · Richard Baraniuk · Andrea Bertozzi · Stanley Osher · Bao Wang
• 2019 : Poster Session »
  Pravish Sainath · Mohamed Akrout · Charles Delahunt · Nathan Kutz · Guangyu Robert Yang · Joseph Marino · L F Abbott · Nicolas Vecoven · Damien Ernst · andrew warrington · Michael Kagan · Kyunghyun Cho · Kameron Harris · Leopold Grinberg · John J. Hopfield · Dmitry Krotov · Taliah Muhammad · Erick Cobos · Edgar Walker · Jacob Reimer · Andreas Tolias · Alexander Ecker · Janaki Sheth · Yu Zhang · Maciej Wołczyk · Jacek Tabor · Szymon Maszke · Roman Pogodin · Dane Corneil · Wulfram Gerstner · Baihan Lin · Guillermo Cecchi · Jenna M Reinen · Irina Rish · Guillaume Bellec · Darjan Salaj · Anand Subramoney · Wolfgang Maass · Yueqi Wang · Ari Pakman · Jin Hyung Lee · Liam Paninski · Bryan Tripp · Colin Graber · Alex Schwing · Luke Prince · Gabriel Ocker · Michael Buice · Benjamin Lansdell · Konrad Kording · Jack Lindsey · Terrence Sejnowski · Matthew Farrell · Eric Shea-Brown · Nicolas Farrugia · Victor Nepveu · Jiwoong Im · Kristin Branson · Brian Hu · Ramakrishnan Iyer · Stefan Mihalas · Sneha Aenugu · Hananel Hazan · Sihui Dai · Tan Nguyen · Doris Tsao · Richard Baraniuk · Anima Anandkumar · Hidenori Tanaka · Aran Nayebi · Stephen Baccus · Surya Ganguli · Dean Pospisil · Eilif Muller · Jeffrey S Cheng · Gaël Varoquaux · Kamalaker Dadi · Dimitrios C Gklezakos · Rajesh PN Rao · Anand Louis · Christos Papadimitriou · Santosh Vempala · Naganand Yadati · Daniel Zdeblick · Daniela M Witten · Nicholas Roberts · Vinay Prabhu · Pierre Bellec · Poornima Ramesh · Jakob H Macke · Santiago Cadena · Guillaume Bellec · Franz Scherr · Owen Marschall · Robert Kim · Hannes Rapp · Marcio Fonseca · Oliver Armitage · Jiwoong Im · Thomas Hardcastle · Abhishek Sharma · Wyeth Bair · Adrian Valente · Shane Shang · Merav Stern · Rutuja Patil · Peter Wang · Sruthi Gorantla · Peter Stratton · Tristan Edwards · Jialin Lu · Martin Ester · Yurii Vlasov · Siavash Golkar
• 2019 : Opening Remarks »
  Reinhard Heckel · Paul Hand · Alex Dimakis · Joan Bruna · Deanna Needell · Richard Baraniuk
• 2019 Workshop: Solving inverse problems with deep networks: New architectures, theoretical foundations, and applications »
  Reinhard Heckel · Paul Hand · Richard Baraniuk · Joan Bruna · Alex Dimakis · Deanna Needell
• 2019 Poster: The Geometry of Deep Networks: Power Diagram Subdivision »
  Randall Balestriero · Romain Cosentino · Behnaam Aazhang · Richard Baraniuk
• 2018 Workshop: Integration of Deep Learning Theories »
  Richard Baraniuk · Anima Anandkumar · Stephane Mallat · Ankit Patel · nhật Hồ
• 2018 : Panel Discussion »
  Richard Baraniuk · Maarten V. de Hoop · Paul A Johnson
• 2018 : Introduction »
  Laura Pyrak-Nolte · James Rustad · Richard Baraniuk
• 2018 Workshop: Machine Learning for Geophysical & Geochemical Signals »
  Laura Pyrak-Nolte · James Rustad · Richard Baraniuk
• 2017 Workshop: Advances in Modeling and Learning Interactions from Complex Data »
  Gautam Dasarathy · Mladen Kolar · Richard Baraniuk
• 2017 Poster: Learned D-AMP: Principled Neural Network based Compressive Image Recovery »
  Chris Metzler · Ali Mousavi · Richard Baraniuk
• 2016 Workshop: Machine Learning for Education »
  Richard Baraniuk · Jiquan Ngiam · Christoph Studer · Phillip Grimaldi · Andrew Lan
• 2016 Poster: A Probabilistic Framework for Deep Learning »
  Ankit Patel · Tan Nguyen · Richard Baraniuk
• 2015 : Probabilistic Theory of Deep Learning »
  Richard Baraniuk
• 2014 Workshop: Human Propelled Machine Learning »
  Richard Baraniuk · Michael Mozer · Divyanshu Vats · Christoph Studer · Andrew E Waters · Andrew Lan
• 2013 Poster: When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated Measurements »
  Divyanshu Vats · Richard Baraniuk
• 2011 Poster: SpaRCS: Recovering low-rank and sparse matrices from compressive measurements »
  Andrew E Waters · Aswin C Sankaranarayanan · Richard Baraniuk
• 2009 Workshop: Manifolds, sparsity, and structured models: When can low-dimensional geometry really help? »
  Richard Baraniuk · Volkan Cevher · Mark A Davenport · Piotr Indyk · Bruno Olshausen · Michael B Wakin
• 2008 Poster: Sparse Signal Recovery Using Markov Random Fields »
  Volkan Cevher · Marco F Duarte · Chinmay Hegde · Richard Baraniuk
• 2008 Spotlight: Sparse Signal Recovery Using Markov Random Fields »
  Volkan Cevher · Marco F Duarte · Chinmay Hegde · Richard Baraniuk
• 2007 Poster: Random Projections for Manifold Learning »
  Chinmay Hegde · Richard Baraniuk