• 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 19 matches

• 2020
• 
  Lu Lu, Xuhui Meng, Zhiping Mao, George Em Karniadakis:
  DeepXDE: A Deep Learning Library for Solving Differential Equations. AAAI Spring Symposium: MLPS 2020
• 
  Adam Collins, Katherine L. Brodie, Andrew Spicer Bak, Tyler J. Hesser, Matthew W. Farthing, Douglas W. Gamble, Joseph W. Long:
  A 2D Fully Convolutional Neural Network for Nearshore And Surf-Zone Bathymetry Inversion from Synthetic Imagery of Surf-Zone using the Model Celeris. AAAI Spring Symposium: MLPS 2020
• 
  Marta D'Elia, George E. Karniadakis, Guofei Pang, Michael L. Parks:
  Nonlocal Physics-Informed Neural Networks - A Unified Theoretical and Computational Framework for Nonlocal Models. AAAI Spring Symposium: MLPS 2020
• 
  Marco Di Giovanni, David Sondak, Pavlos Protopapas, Marco Brambilla:
  Finding Multiple Solutions of ODEs with Neural Networks. AAAI Spring Symposium: MLPS 2020
• 
  Ashkan Haji Hosseinloo, Munther A. Dahleh:
  Event-Triggered Reinforcement Learning; An Application to Buildings' Micro-Climate Control. AAAI Spring Symposium: MLPS 2020
• 
  Jonghyun Lee, Eric F. Darve, Peter K. Kitanidis, Matthew W. Farthing, Tyler J. Hesser:
  Preface. AAAI Spring Symposium: MLPS 2020
• 
  Leixin Ma, Themistocles Resvanis, Kim Vandiver:
  A Weighted Sparse-Input Neural Network Technique Applied to Identify Important Features for Vortex-Induced Vibration. AAAI Spring Symposium: MLPS 2020
• 
  Anishi Mehta, Cory Braker Scott, Diane Oyen, Nishant Panda, Gowri Srinivasan:
  Physics-Informed Spatiotemporal Deep Learning for Emulating Coupled Dynamical Systems. AAAI Spring Symposium: MLPS 2020
• 
  Maruti Kumar Mudunuru, Daniel O'Malley, Shriram Srinivasan, Jeffrey D. Hyman, Matthew R. Sweeney, Luke Frash, Bill Carey, Michael R. Gross, Nathan J. Welch, Satish Karra, Velimir V. Vesselinov, Qinjun Kang, Hongwu Xu, Rajesh J. Pawar, Tim Carr, Liwei Li, George D. Guthrie, Hari S. Viswanathan:
  Physics-Informed Machine Learning for Real-time Reservoir Management. AAAI Spring Symposium: MLPS 2020
• 
  Anton Nikolaev, Ingo Richter, Peter Sadowski:
  Deep Learning for Climate Models of the Atlantic Ocean. AAAI Spring Symposium: MLPS 2020
• 
  Yizhou Qian, Hojat Ghorbanidehno, Matthew W. Farthing, Ty Hesser, Peter K. Kitanidis, Eric F. Darve:
  Surfzone Topography-informed Deep Learning Techniques to Nearshore Bathymetry with Sparse Measurements. AAAI Spring Symposium: MLPS 2020
• 
  Brandon Quach, Yannik Glaser, Justin Stopa, Peter J. Sadowski:
  Deep Sensing of Ocean Wave Heights with Synthetic Aperture Radar. AAAI Spring Symposium: MLPS 2020
• 
  Christopher Rackauckas, Alan Edelman, Keno Fischer, Mike Innes, Elliot Saba, Viral B. Shah, Will Tebbutt:
  Generalized Physics-Informed Learning through Language-Wide Differentiable Programming. AAAI Spring Symposium: MLPS 2020
• 
  Panos Stinis:
  Enforcing Constraints for Time Series Prediction in Supervised, Unsupervised and Reinforcement Learning. AAAI Spring Symposium: MLPS 2020
• 
  Mohammadamin Tavakoli, Pierre Baldi:
  Continuous Representation of Molecules using Graph Variational Autoencoder. AAAI Spring Symposium: MLPS 2020
• 
  Nathaniel Trask, Ravi G. Patel, Paul J. Atzberger, Ben J. Gross:
  GMLS-Nets: A Machine Learning Framework for Unstructured Data. AAAI Spring Symposium: MLPS 2020
• 
  Kailai Xu, Eric Darve:
  Data-Driven Inverse Modeling with Incomplete Observations. AAAI Spring Symposium: MLPS 2020
• 
  Hongkyu Yoon, Darryl J. Melander, Stephen J. Verzi:
  Permeability Prediction of Porous Media using Convolutional Neural Networks with Physical Properties. AAAI Spring Symposium: MLPS 2020
• 
  Jonghyun Lee, Eric F. Darve, Peter K. Kitanidis, Matthew W. Farthing, Tyler J. Hesser:
  Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to - 25th, 2020. CEUR Workshop Proceedings 2587, CEUR-WS.org 2020 [contents]