default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDAtilim Günes Baydin
Atilim Gunes Baydin
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[i55]Giacomo Acciarini, Atilim Günes Baydin, Dario Izzo:
Closing the Gap Between SGP4 and High-Precision Propagation via Differentiable Programming. CoRR abs/2402.04830 (2024)- [i54]Adam D. Cobb, Atilim Günes Baydin, Barak A. Pearlmutter, Susmit Jha:
Second-Order Forward-Mode Automatic Differentiation for Optimization. CoRR abs/2408.10419 (2024) - [i53]James Walsh, Daniel G. Gass, Raúl Ramos-Pollán, Paul J. Wright, Richard Galvez, Noah Kasmanoff, Jason Naradowsky, Anne Spalding, James Parr, Atilim Günes Baydin:
A Foundation Model for the Solar Dynamics Observatory. CoRR abs/2410.02530 (2024) - [i52]Rutuja Gurav, Elena Massara, Xiaomei Song, Kimberly Sinclair, Edward Brown, Matt Kusner, Bala Poduval, Atilim Gunes Baydin:
Probabilistic Forecasting of Radiation Exposure for Spaceflight. CoRR abs/2411.17703 (2024) - [i51]Sam A. Scivier, Tarje Nissen-Meyer, Paula Koelemeijer, Atilim Günes Baydin:
Gaussian Processes for Probabilistic Estimates of Earthquake Ground Shaking: A 1-D Proof-of-Concept. CoRR abs/2412.03299 (2024) - 2023
- [i50]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 A. 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 abs/2310.17688 (2023) - [i49]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 abs/2312.06845 (2023) - 2022
- [c16]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:
Amortized Rejection Sampling in Universal Probabilistic Programming. AISTATS 2022: 8392-8412 - [c15]A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Gunes Baydin:
KL Guided Domain Adaptation. ICLR 2022 - [c14]William Harvey, Andreas Munk, Atilim Günes Baydin, Alexander Bergholm, Frank Wood:
Attention for Inference Compilation. SIMULTECH 2022: 80-91 - [c13]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: 1423-1433 - [i48]Atilim Günes Baydin, Barak A. Pearlmutter, Don Syme, Frank Wood, Philip H. S. Torr:
Gradients without Backpropagation. CoRR abs/2202.08587 (2022) - [i47]Valentina Salvatelli, Luiz F. G. dos Santos, Souvik Bose, Brad Neuberg, Mark C. M. Cheung, Miho Janvier, Meng Jin, Yarin Gal, Atilim Gunes Baydin:
Exploring the Limits of Synthetic Creation of Solar EUV Images via Image-to-Image Translation. CoRR abs/2208.09512 (2022) - 2021
- [c12]A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin:
Domain Invariant Representation Learning with Domain Density Transformations. NeurIPS 2021: 5264-5275 - [i46]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 abs/2101.03989 (2021) - [i45]A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Günes Baydin:
Domain Invariant Representation Learning with Domain Density Transformations. CoRR abs/2102.05082 (2021) - [i44]A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atilim Günes Baydin:
KL Guided Domain Adaptation. CoRR abs/2106.07780 (2021) - [i43]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 abs/2110.02483 (2021) - [i42]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 H. 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 abs/2112.03235 (2021) - [i41]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 abs/2112.09051 (2021) - 2020
- [c11]Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet:
AutoSimulate: (Quickly) Learning Synthetic Data Generation. ECCV (22) 2020: 255-271 - [c10]Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atilim Gunes Baydin:
Black-Box Optimization with Local Generative Surrogates. NeurIPS 2020 - [d1]Andrés Muñoz-Jaramillo
, Xavier Gitiaux, Anna Jungbluth, Shane A. Maloney, Carl Shneider, Paul J. Wright, Michel Deudon, Alfredo Kalaitzis, Atilim Günes Baydin, Yarin Gal:
Converter software to calibrate and super-resolve solar magnetograms. Zenodo, 2020
- [i40]Sergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atilim Günes Baydin:
Differentiating the Black-Box: Optimization with Local Generative Surrogates. CoRR abs/2002.04632 (2020) - [i39]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 abs/2005.07062 (2020) - [i38]Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet:
AutoSimulate: (Quickly) Learning Synthetic Data Generation. CoRR abs/2008.08424 (2020) - [i37]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 abs/2012.10260 (2020) - [i36]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 abs/2012.12450 (2020) - [i35]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 abs/2012.14023 (2020)
2010 – 2019
- 2019
- [c9]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:
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. NeurIPS 2019: 5460-5473 - [c8]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:
Usability of Probabilistic Programming Languages. PPIG 2019 - [c7]Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas 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: 29:1-29:24 - [i34]Harkirat Singh Behl, Atilim Günes Baydin, Philip H. S. Torr:
Alpha MAML: Adaptive Model-Agnostic Meta-Learning. CoRR abs/1905.07435 (2019) - [i33]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 abs/1905.10659 (2019) - [i32]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 abs/1905.12432 (2019) - [i31]Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas 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 abs/1907.03382 (2019) - [i30]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 abs/1910.01570 (2019) - [i29]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 abs/1910.03019 (2019) - [i28]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 abs/1910.03085 (2019) - [i27]Adam D. Cobb, Atilim Günes Baydin, Andrew Markham, Stephen J. Roberts:
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo. CoRR abs/1910.06243 (2019) - [i26]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 abs/1910.09056 (2019) - [i25]Andreas Munk, Adam Scibior, Atilim Günes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood:
Deep Probabilistic Surrogate Networks for Universal Simulator Approximation. CoRR abs/1910.11950 (2019) - [i24]William Harvey, Andreas Munk, Atilim Günes Baydin, Alexander Bergholm, Frank Wood:
Attention for Inference Compilation. CoRR abs/1910.11961 (2019) - [i23]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 abs/1911.01486 (2019) - [i22]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 abs/1911.01490 (2019) - [i21]Valentina Salvatelli, Souvik Bose, Brad Neuberg, Luiz F. G. dos Santos, Mark C. M. Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin:
Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona. CoRR abs/1911.04006 (2019) - [i20]Brad Neuberg, Souvik Bose, Valentina Salvatelli, Luiz F. G. dos Santos, Mark C. M. Cheung, Miho Janvier, Atilim Gunes Baydin, Yarin Gal, Meng Jin:
Auto-Calibration of Remote Sensing Solar Telescopes with Deep Learning. CoRR abs/1911.04008 (2019) - [i19]Andrew Gambardella, Atilim Günes Baydin, Philip H. S. Torr:
Transflow Learning: Repurposing Flow Models Without Retraining. CoRR abs/1911.13270 (2019) - 2018
- [c6]Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank Wood:
Online Learning Rate Adaptation with Hypergradient Descent. ICLR (Poster) 2018 - [i18]Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank D. Wood:
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. CoRR abs/1807.07706 (2018) - [i17]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:
Bayesian Deep Learning for Exoplanet Atmospheric Retrieval. CoRR abs/1811.03390 (2018) - 2017
- [j3]Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul, Jeffrey Mark Siskind:
Automatic Differentiation in Machine Learning: a Survey. J. Mach. Learn. Res. 18: 153:1-153:43 (2017) - [c5]Tuan Anh Le, Atilim Gunes Baydin, Frank D. Wood:
Inference Compilation and Universal Probabilistic Programming. AISTATS 2017: 1338-1348 - [c4]Tuan Anh Le, Atilim Günes Baydin, Robert Zinkov, Frank D. Wood:
Using synthetic data to train neural networks is model-based reasoning. IJCNN 2017: 3514-3521 - [i16]Tuan Anh Le, Atilim Gunes Baydin, Robert Zinkov, Frank D. Wood:
Using Synthetic Data to Train Neural Networks is Model-Based Reasoning. CoRR abs/1703.00868 (2017) - [i15]Atilim Gunes Baydin, Robert Cornish, David Martínez-Rubio, Mark Schmidt, Frank D. Wood:
Online Learning Rate Adaptation with Hypergradient Descent. CoRR abs/1703.04782 (2017) - [i14]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:
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators. CoRR abs/1712.07901 (2017) - 2016
- [i13]Tuan Anh Le, Atilim Gunes Baydin, Frank D. Wood:
Inference Compilation and Universal Probabilistic Programming. CoRR abs/1610.09900 (2016) - [i12]Atilim Günes Baydin, Barak A. Pearlmutter, Jeffrey Mark Siskind:
DiffSharp: An AD Library for .NET Languages. CoRR abs/1611.03423 (2016) - [i11]Atilim Günes Baydin, Barak A. Pearlmutter, Jeffrey Mark Siskind:
Tricks from Deep Learning. CoRR abs/1611.03777 (2016) - 2015
- [j2]Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón:
A semantic network-based evolutionary algorithm for computational creativity. Evol. Intell. 8(1): 3-21 (2015) - [i10]Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul:
Automatic differentiation in machine learning: a survey. CoRR abs/1502.05767 (2015) - [i9]Atilim Gunes Baydin, Barak A. Pearlmutter, Jeffrey Mark Siskind:
DiffSharp: Automatic Differentiation Library. CoRR abs/1511.07727 (2015) - 2014
- [i8]Atilim Gunes Baydin, Barak A. Pearlmutter:
Automatic Differentiation of Algorithms for Machine Learning. CoRR abs/1404.7456 (2014) - [i7]Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón:
A semantic network-based evolutionary algorithm for modeling memetic evolution and creativity. CoRR abs/1404.7765 (2014) - [i6]Atilim Gunes Baydin, Barak A. Pearlmutter:
An Analysis of Publication Venues for Automatic Differentiation Research. CoRR abs/1409.7316 (2014) - 2013
- [i5]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 abs/1304.1609 (2013) - 2012
- [j1]Atilim Günes Baydin:
Evolution of central pattern generators for the control of a five-link bipedal walking mechanism. Paladyn J. Behav. Robotics 3(1): 45-53 (2012) - [c3]Atilim Günes Baydin, Ramón López de Mántaras:
Evolution of ideas: A novel memetic algorithm based on semantic networks. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c2]Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón:
Automated Generation of Cross-Domain Analogies via Evolutionary Computation. ICCC 2012: 25-32 - [i4]Atilim Günes Baydin, Ramón López de Mántaras:
Evolution of Ideas: A Novel Memetic Algorithm Based on Semantic Networks. CoRR abs/1201.2706 (2012) - [i3]Atilim Günes Baydin, Ramón López de Mántaras, Santiago Ontañón:
Automated Generation of Cross-Domain Analogies via Evolutionary Computation. CoRR abs/1204.2335 (2012) - 2011
- [c1]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: 378-392 - [i2]Atilim Günes Baydin, Ramón López de Mántaras, Simeon J. Simoff, Carles Sierra:
CBR with Commonsense Reasoning and Structure Mapping: An Application to Mediation. CoRR abs/1108.0039 (2011)
2000 – 2009
- 2008
- [i1]Atilim Günes Baydin:
Evolution of central pattern generators for the control of a five-link planar bipedal walking mechanism. CoRR abs/0801.0830 (2008)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-27 21:48 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
