Atilim Günes Baydin

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 37

Top Topics

Evolutionary Algorithm

Risk Assessment

Neural Network Ensembles

Invariant Representation

Top Venues

Publications

Giacomo Acciarini, Atilim Günes Baydin, Dario Izzo
Closing the Gap Between SGP4 and High-Precision Propagation via Differentiable Programming. CoRR (2024)
Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann
Managing AI Risks in an Era of Rapid Progress. CoRR (2023)
Shreshth A. Malik, James Walsh, Giacomo Acciarini, Thomas E. Berger, Atilim Günes Baydin
High-Cadence Thermospheric Density Estimation enabled by Machine Learning on Solar Imagery. CoRR (2023)
Atilim Günes Baydin, Barak A. Pearlmutter, Don Syme, Frank Wood, Philip H. S. Torr
Gradients without Backpropagation. CoRR (2022)
William Harvey, Andreas Munk, Atilim Günes Baydin, Alexander Bergholm, Frank Wood
Attention for Inference Compilation. SIMULTECH (2022)
Andreas Munk, Berend Zwartsenberg, Adam Scibior, Atilim Günes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood
Probabilistic surrogate networks for simulators with unbounded randomness. UAI (2022)
A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Günes Baydin
Domain Invariant Representation Learning with Domain Density Transformations. CoRR (2021)
Andrew Gambardella, Bogdan State, Naeemullah Khan, Leo Tsourides, Philip H. S. Torr, Atilim Günes Baydin
Detecting and Quantifying Malicious Activity with Simulation-based Inference. CoRR (2021)
Bernard Benson, Edward Brown, Stefano Bonasera, Giacomo Acciarini, Jorge A. Pérez-Hernández, Eric Sutton, Moriba K. Jah, Christopher Bridges, Meng Jin, Atilim Günes Baydin
Simultaneous Multivariate Forecast of Space Weather Indices using Deep Neural Network Ensembles. CoRR (2021)
Alexander Lavin, Hector Zenil, Brooks Paige, David Krakauer, Justin Gottschlich, Tim Mattson, Anima Anandkumar, Sanjay Choudry, Kamil Rocki, Atilim Günes Baydin, Carina Prunkl, Olexandr Isayev, Erik Peterson, Peter L. McMahon, Jakob Macke, Kyle Cranmer, Jiaxin Zhang, Haruko M. Wainwright, Adi Hanuka, Manuela Veloso, Samuel Assefa, Stephan Zheng, Avi Pfeffer
Simulation Intelligence: Towards a New Generation of Scientific Methods. CoRR (2021)
Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atilim Günes Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr
Technology Readiness Levels for Machine Learning Systems. CoRR (2021)
A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Günes Baydin
KL Guided Domain Adaptation. CoRR (2021)
Christian Schröder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Robert Zinkov, Puneet K. Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip H. S. Torr, Atilim Günes Baydin
Simulation-Based Inference for Global Health Decisions. CoRR (2020)
Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet
AutoSimulate: (Quickly) Learning Synthetic Data Generation. ECCV (22) (2020)
Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atilim Günes Baydin
Differentiating the Black-Box: Optimization with Local Generative Surrogates. CoRR (2020)
Francesco Pinto, Giacomo Acciarini, Sascha Metz, Sarah Boufelja, Sylvester Kaczmarek, Klaus Merz, José A. Martinez-Heras, Francesca Letizia, Christopher Bridges, Atilim Günes Baydin
Towards Automated Satellite Conjunction Management with Bayesian Deep Learning. CoRR (2020)
Luiz F. G. dos Santos, Souvik Bose, Valentina Salvatelli, Brad Neuberg, Mark C. M. Cheung, Miho Janvier, Meng Jin, Yarin Gal, Paul Boerner, Atilim Günes Baydin
Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning. CoRR (2020)
Giacomo Acciarini, Francesco Pinto, Sascha Metz, Sarah Boufelja, Sylvester Kaczmarek, Klaus Merz, José A. Martinez-Heras, Francesca Letizia, Christopher Bridges, Atilim Günes Baydin
Spacecraft Collision Risk Assessment with Probabilistic Programming. CoRR (2020)
Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet
AutoSimulate: (Quickly) Learning Synthetic Data Generation. CoRR (2020)
Anna Jungbluth, Xavier Gitiaux, Shane A. Maloney, Carl Shneider, Paul J. Wright, Alfredo Kalaitzis, Michel Deudon, Atilim Günes Baydin, Yarin Gal, Andrés Muñoz-Jaramillo
Single-Frame Super-Resolution of Solar Magnetograms: Investigating Physics-Based Metrics \& Losses. CoRR (2019)
Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale. CoRR (2019)
Gonzalo Mateo-Garcia, Silviu Oprea, Lewis Smith, Josh Veitch-Michaelis, Guy Schumann, Yarin Gal, Atilim Günes Baydin, Dietmar Backes
Flood Detection On Low Cost Orbital Hardware. CoRR (2019)
Adam D. Cobb, Michael D. Himes, Frank Soboczenski, Simone Zorzan, Molly D. O'Beirne, Atilim Günes Baydin, Yarin Gal, Shawn D. Domagal-Goldman, Giada N. Arney, Daniel Angerhausen
An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval. CoRR (2019)
Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Etalumis: bringing probabilistic programming to scientific simulators at scale. SC (2019)
Andrew Gambardella, Atilim Günes Baydin, Philip H. S. Torr
Transflow Learning: Repurposing Flow Models Without Retraining. CoRR (2019)
Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Günes Baydin, Bradley Gram-Hansen, Christian Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood
Amortized Rejection Sampling in Universal Probabilistic Programming. CoRR (2019)
Bradley Gram-Hansen, Christian Schröder de Witt, Tom Rainforth, Philip H. S. Torr, Yee Whye Teh, Atilim Günes Baydin
Hijacking Malaria Simulators with Probabilistic Programming. CoRR (2019)
Adam D. Cobb, Atilim Günes Baydin, Andrew Markham, Stephen J. Roberts
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo. CoRR (2019)
Harkirat Singh Behl, Atilim Günes Baydin, Philip H. S. Torr
Alpha MAML: Adaptive Model-Agnostic Meta-Learning. CoRR (2019)
Kara Lamb, Garima Malhotra, Athanasios Vlontzos, Edward Wagstaff, Atilim Günes Baydin, Anahita Bhiwandiwalla, Yarin Gal, Alfredo Kalaitzis, Anthony Reina, Asti Bhatt
Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder. CoRR (2019)
William Harvey, Andreas Munk, Atilim Günes Baydin, Alexander Bergholm, Frank Wood
Attention for Inference Compilation. CoRR (2019)
Kara Lamb, Garima Malhotra, Athanasios Vlontzos, Edward Wagstaff, Atilim Günes Baydin, Anahita Bhiwandiwalla, Yarin Gal, Alfredo Kalaitzis, Anthony Reina, Asti Bhatt
Prediction of GNSS Phase Scintillations: A Machine Learning Approach. CoRR (2019)
Andreas Munk, Adam Scibior, Atilim Günes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood
Deep Probabilistic Surrogate Networks for Universal Simulator Approximation. CoRR (2019)
Xavier Gitiaux, Shane A. Maloney, Anna Jungbluth, Carl Shneider, Paul J. Wright, Atilim Günes Baydin, Michel Deudon, Yarin Gal, Alfredo Kalaitzis, Andrés Muñoz-Jaramillo
Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties. CoRR (2019)
Tuan Anh Le, Atilim Günes Baydin, Robert Zinkov, Frank D. Wood
Using synthetic data to train neural networks is model-based reasoning. IJCNN (2017)
Atilim Günes Baydin, Barak A. Pearlmutter, Jeffrey Mark Siskind
Tricks from Deep Learning. CoRR (2016)
Atilim Günes Baydin, Barak A. Pearlmutter, Jeffrey Mark Siskind
DiffSharp: An AD Library for .NET Languages. CoRR (2016)
Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón
A semantic network-based evolutionary algorithm for computational creativity. Evol. Intell. 8 (1) (2015)
Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón
A semantic network-based evolutionary algorithm for modeling memetic evolution and creativity. CoRR (2014)
Melek Tendurus, Atilim Günes Baydin, Marieke A. Eleveld, Alison J. Gilbert
City versus wetland: Predicting urban growth in the Vecht area with a cellular automaton model CoRR (2013)
Atilim Günes Baydin, Ramón López de Mántaras
Evolution of Ideas: A Novel Memetic Algorithm Based on Semantic Networks CoRR (2012)
Atilim Günes Baydin
Evolution of central pattern generators for the control of a five-link bipedal walking mechanism. Paladyn J. Behav. Robotics 3 (1) (2012)
Atilim Günes Baydin, Ramón López de Mántaras
Evolution of ideas: A novel memetic algorithm based on semantic networks. IEEE Congress on Evolutionary Computation (2012)
Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón
Automated Generation of Cross-Domain Analogies via Evolutionary Computation. ICCC (2012)
Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón
Automated Generation of Cross-Domain Analogies via Evolutionary Computation CoRR (2012)
Atilim Günes Baydin, Ramón López de Mántaras, Simeon J. Simoff, Carles Sierra
CBR with Commonsense Reasoning and Structure Mapping: An Application to Mediation CoRR (2011)
Atilim Günes Baydin, Ramón López de Mántaras, Simeon J. Simoff, Carles Sierra
CBR with Commonsense Reasoning and Structure Mapping: An Application to Mediation. ICCBR (2011)
Atilim Günes Baydin
Evolution of central pattern generators for the control of a five-link planar bipedal walking mechanism CoRR (2008)