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ORCIDDilan Görür
Person information
- affiliation: DeepMind, Mountain View, CA, USA
- affiliation (former): Max Planck Institute for Informatics, Saarbücken, Germany
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2020 – today
- 2024
[i10]Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulos, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim:
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR abs/2407.12687 (2024)- [i9]Arslan Chaudhry, Sridhar Thiagarajan, Dilan Görür:
Finetuning Language Models to Emit Linguistic Expressions of Uncertainty. CoRR abs/2409.12180 (2024) - 2023
- [c14]Jiefeng Chen, Timothy Nguyen, Dilan Görür, Arslan Chaudhry:
Is Forgetting Less a Good Inductive Bias for Forward Transfer? ICLR 2023 - [i8]Jiefeng Chen, Timothy Nguyen, Dilan Görür, Arslan Chaudhry:
Is forgetting less a good inductive bias for forward transfer? CoRR abs/2303.08207 (2023) - 2022
- [c13]Seyed-Iman Mirzadeh, Arslan Chaudhry, Dong Yin, Huiyi Hu, Razvan Pascanu, Dilan Görür, Mehrdad Farajtabar:
Wide Neural Networks Forget Less Catastrophically. ICML 2022: 15699-15717 - [i7]Seyed-Iman Mirzadeh, Arslan Chaudhry, Dong Yin, Timothy Nguyen, Razvan Pascanu, Dilan Görür, Mehrdad Farajtabar:
Architecture Matters in Continual Learning. CoRR abs/2202.00275 (2022) - 2021
- [c12]Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Dilan Görür, Razvan Pascanu, Hassan Ghasemzadeh:
Linear Mode Connectivity in Multitask and Continual Learning. ICLR 2021 - [i6]Seyed-Iman Mirzadeh, Arslan Chaudhry, Huiyi Hu, Razvan Pascanu, Dilan Görür, Mehrdad Farajtabar:
Wide Neural Networks Forget Less Catastrophically. CoRR abs/2110.11526 (2021) - [i5]Huiyi Hu, Ang Li, Daniele Calandriello, Dilan Görür:
One Pass ImageNet. CoRR abs/2111.01956 (2021) - 2020
- [c11]Nevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Görür, Chris Harris, Dale Schuurmans:
A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs. NeurIPS 2020 - [i4]Nevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Görür, Chris Harris, Dale Schuurmans:
A maximum-entropy approach to off-policy evaluation in average-reward MDPs. CoRR abs/2006.12620 (2020) - [i3]Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Dilan Görür, Razvan Pascanu, Hassan Ghasemzadeh:
Linear Mode Connectivity in Multitask and Continual Learning. CoRR abs/2010.04495 (2020)
2010 – 2019
- 2019
- [c10]Eric T. Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Görür, Balaji Lakshminarayanan:
Do Deep Generative Models Know What They Don't Know? ICLR (Poster) 2019 - [c9]Eric T. Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Görür, Balaji Lakshminarayanan:
Hybrid Models with Deep and Invertible Features. ICML 2019: 4723-4732 - [i2]Eric T. Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Görür, Balaji Lakshminarayanan:
Hybrid Models with Deep and Invertible Features. CoRR abs/1902.02767 (2019) - 2018
- [i1]Eric T. Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Görür, Balaji Lakshminarayanan:
Do Deep Generative Models Know What They Don't Know? CoRR abs/1810.09136 (2018) - 2012
- [c8]Dilan Görür, Levi Boyles, Max Welling:
Scalable Inference on Kingman's Coalescent using Pair Similarity . AISTATS 2012: 440-448 - 2010
- [j1]Dilan Görür, Carl Edward Rasmussen:
Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution. J. Comput. Sci. Technol. 25(4): 653-664 (2010)
2000 – 2009
- 2009
- [c7]Yee Whye Teh, Dilan Görür:
Indian Buffet Processes with Power-law Behavior. NIPS 2009: 1838-1846 - [c6]Katherine A. Heller, Yee Whye Teh, Dilan Görür:
Infinite Hierarchical Hidden Markov Models. AISTATS 2009: 224-231 - 2008
- [c5]Jan Gasthaus, Frank D. Wood, Dilan Görür, Yee Whye Teh:
Dependent Dirichlet Process Spike Sorting. NIPS 2008: 497-504 - [c4]Dilan Görür, Yee Whye Teh:
An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering. NIPS 2008: 521-528 - 2007
- [b1]Dilan Görür:
Nonparametric Bayesian discrete latent variable models for unsupervised learning. Berlin Institute of Technology, 2007 - [c3]Yee Whye Teh, Dilan Görür, Zoubin Ghahramani:
Stick-breaking Construction for the Indian Buffet Process. AISTATS 2007: 556-563 - 2006
- [c2]Dilan Görür, Frank Jäkel, Carl Edward Rasmussen:
A choice model with infinitely many latent features. ICML 2006: 361-368 - 2004
- [c1]Dilan Görür, Carl Edward Rasmussen, Andreas S. Tolias, Fabian H. Sinz, Nikos K. Logothetis:
Modelling Spikes with Mixtures of Factor Analysers. DAGM-Symposium 2004: 391-398
Coauthor Index
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