Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

Exploring the Limits of Synthetic Creation of Solar EUV Images via Image-to-Image Translation


Aug 19, 2022
Valentina Salvatelli, Luiz F. G. dos Santos, Souvik Bose, Brad Neuberg, Mark C. M. Cheung, Miho Janvier, Meng Jin, Yarin Gal, Atilim Gunes Baydin

* 16 pages, 8 figures. To be published on ApJ (submitted on Feb 21st, accepted on July 28th) 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Domain Invariant Representation Learning with Domain Density Transformations


Feb 09, 2021
A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin


   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning


Nov 10, 2019
Brad Neuberg, Souvik Bose, Valentina Salvatelli, Luiz F. G. dos Santos, Mark Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin

* 6 pages, 3 figures, Accepted at NeurIPS 2019 Workshop ML4PS 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona


Nov 10, 2019
Valentina Salvatelli, Souvik Bose, Brad Neuberg, Luiz F. G. dos Santos, Mark Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin

* 5 pages, 6 figures, Accepted at the NeurIPS 2019 Workshop ML4PS 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Bayesian Deep Learning for Exoplanet Atmospheric Retrieval


Dec 02, 2018
Frank Soboczenski, Michael D. Himes, Molly D. O'Beirne, Simone Zorzan, Atilim Gunes Baydin, Adam D. Cobb, Yarin Gal, Daniel Angerhausen, Massimo Mascaro, Giada N. Arney, Shawn D. Domagal-Goldman

* Third workshop on Bayesian Deep Learning (NeurIPS 2018), Montreal, Canada 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model


Sep 01, 2018
Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank Wood

* 18 pages, 5 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Online Learning Rate Adaptation with Hypergradient Descent


Feb 26, 2018
Atilim Gunes Baydin, Robert Cornish, David Martinez Rubio, Mark Schmidt, Frank Wood

* In Sixth International Conference on Learning Representations (ICLR), Vancouver, Canada, April 30 -- May 3, 2018. https://openreview.net/forum?id=BkrsAzWAb 
* 11 pages, 4 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Automatic differentiation in machine learning: a survey


Feb 05, 2018
Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul, Jeffrey Mark Siskind

* Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul, Jeffrey Mark Siskind. Automatic differentiation in machine learning: a survey. The Journal of Machine Learning Research, 18(153):1--43, 2018 
* 43 pages, 5 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators


Dec 21, 2017
Mario Lezcano Casado, Atilim Gunes Baydin, David Martinez Rubio, Tuan Anh Le, Frank Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat

* 7 pages, 2 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Using Synthetic Data to Train Neural Networks is Model-Based Reasoning


Mar 02, 2017
Tuan Anh Le, Atilim Gunes Baydin, Robert Zinkov, Frank Wood

* 8 pages, 4 figures 

   Access Paper or Ask Questions

  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
>>