Atilim Gunes Baydin

24 papers A* 4A 2Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Probabilistic Forecasting of Radiation Exposure for Spaceflight. CoRR Rutuja Gurav, Elena Massara, Xiaomei Song, Kimberly Sinclair, Edward Brown, Matt J. Kusner, Bala Poduval, Atilim Gunes Baydin
2022	A	`conf`	Amortized Rejection Sampling in Universal Probabilistic Programming. AISTATS Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood
2022	J	`jnl`	Exploring the Limits of Synthetic Creation of Solar EUV Images via Image-to-Image Translation. CoRR Valentina Salvatelli, Luiz F. G. dos Santos, Souvik Bose, Brad Neuberg, Mark C. M. Cheung, Miho Janvier, Meng Jin, Yarin Gal, Atilim Gunes Baydin
2022	A*	`conf`	KL Guided Domain Adaptation. ICLR A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Gunes Baydin
2021	A*	`conf`	Domain Invariant Representation Learning with Domain Density Transformations. NeurIPS A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin
2020	A*	`conf`	Black-Box Optimization with Local Generative Surrogates. NeurIPS Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atilim Gunes Baydin
2019	J	`jnl`	Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning. CoRR Brad Neuberg, Souvik Bose, Valentina Salvatelli, Luiz F. G. dos Santos, Mark C. M. Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin
2019	A*	`conf`	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. NeurIPS Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
2019	—	`conf`	Usability of Probabilistic Programming Languages. PPIG Alan F. Blackwell, Luke Church, Martin Erwig, James Geddes, Andy Gordon, Maria I. Gorinova, Atilim Gunes Baydin, Bradley Gram-Hansen, Tobias Kohn, Neil D. Lawrence, Vikash Mansinghka, Brooks Paige, Tomas Petricek, Diana Robinson, Advait Sarkar, Oliver Strickson
2019	J	`jnl`	Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona. CoRR Valentina Salvatelli, Souvik Bose, Brad Neuberg, Luiz F. G. dos Santos, Mark C. M. Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin
2018	J	`jnl`	Bayesian Deep Learning for Exoplanet Atmospheric Retrieval. CoRR Frank Soboczenski, Michael D. Himes, Molly D. O'Beirne, Simone Zorzan, Atilim Gunes Baydin, Adam D. Cobb, Daniel Angerhausen, Giada N. Arney, Shawn D. Domagal-Goldman
2018	J	`jnl`	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. CoRR Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank D. Wood
2018	—	`conf`	Online Learning Rate Adaptation with Hypergradient Descent. ICLR (Poster) Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank Wood
2017	J	`jnl`	Automatic Differentiation in Machine Learning: a Survey. J. Mach. Learn. Res. Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul, Jeffrey Mark Siskind
2017	J	`jnl`	Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators. CoRR Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez-Rubio, Tuan Anh Le, Frank D. Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat
2017	A	`conf`	Inference Compilation and Universal Probabilistic Programming. AISTATS Tuan Anh Le, Atilim Gunes Baydin, Frank D. Wood
2017	J	`jnl`	Online Learning Rate Adaptation with Hypergradient Descent. CoRR Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank D. Wood
2017	J	`jnl`	Using Synthetic Data to Train Neural Networks is Model-Based Reasoning. CoRR Tuan Anh Le, Atilim Gunes Baydin, Robert Zinkov, Frank D. Wood
2016	J	`jnl`	Inference Compilation and Universal Probabilistic Programming. CoRR Tuan Anh Le, Atilim Gunes Baydin, Frank D. Wood
2015	J	`jnl`	Automatic differentiation in machine learning: a survey. CoRR Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul
2015	J	`jnl`	DiffSharp: Automatic Differentiation Library. CoRR Atilim Gunes Baydin, Barak A. Pearlmutter, Jeffrey Mark Siskind
2014	J	`jnl`	An Analysis of Publication Venues for Automatic Differentiation Research. CoRR Atilim Gunes Baydin, Barak A. Pearlmutter
2014	J	`jnl`	Automatic Differentiation of Algorithms for Machine Learning. CoRR Atilim Gunes Baydin, Barak A. Pearlmutter
2014	—	`—`	Evolut ionary adap tat ion in cas e - bas ed reasoning. An application to cross-domain analogies for mediation. Atilim Gunes Baydin