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ORCIDÇagatay Yildiz
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- unicode name: Çağatay Yıldız
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Books and Theses
- 2022
[b1]Çagatay Yildiz:
Differential Equations for Machine Learning. Aalto University, Espoo, Finland, 2022
Journal Articles
- 2018
- [j2]Baris Kurt
, Çagatay Yildiz, Taha Yusuf Ceritli, Bülent Sankur, Ali Taylan Cemgil:
A Bayesian change point model for detecting SIP-based DDoS attacks. Digit. Signal Process. 77: 48-62 (2018) - [j1]Çagatay Yildiz, Baris Kurt, Taha Yusuf Ceritli, Bülent Sankur, Ali Taylan Cemgil:
A real-time SIP network simulation and monitoring system. SoftwareX 8: 21-25 (2018)
Conference and Workshop Papers
- 2023
- [c12]Valerii Iakovlev, Çagatay Yildiz, Markus Heinonen, Harri Lähdesmäki:
Latent Neural ODEs with Sparse Bayesian Multiple Shooting. ICLR 2023 - [c11]Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves:
Modulated Neural ODEs. NeurIPS 2023 - 2022
- [c10]Çagatay Yildiz, Melih Kandemir, Barbara Rakitsch:
Learning interacting dynamical systems with latent Gaussian process ODEs. NeurIPS 2022 - [c9]Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen:
Variational multiple shooting for Bayesian ODEs with Gaussian processes. UAI 2022: 790-799 - 2021
- [c8]Çagatay Yildiz, Markus Heinonen, Harri Lähdesmäki:
Continuous-time Model-based Reinforcement Learning. ICML 2021: 12009-12018 - 2019
- [c7]Çagatay Yildiz, Markus Heinonen, Harri Lähdesmäki:
ODE2VAE: Deep generative second order ODEs with Bayesian neural networks. NeurIPS 2019: 13412-13421 - 2018
- [c6]Markus Heinonen, Çagatay Yildiz, Henrik Mannerström, Jukka Intosalmi, Harri Lähdesmäki:
Learning unknown ODE models with Gaussian processes. ICML 2018: 1964-1973 - [c5]Umut Simsekli, Çagatay Yildiz, Thanh Huy Nguyen, A. Taylan Cemgil, Gaël Richard:
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization. ICML 2018: 4681-4690 - [c4]Çagatay Yildiz, Markus Heinonen, Jukka Intosalmi, Henrik Mannerström, Harri Lähdesmäki:
Learning stochastic differential equations with Gaussian Processes without Gradient Matching. MLSP 2018: 1-6 - 2017
- [c3]Çagatay Yildiz, Haluk O. Bingol, Gulcin Irim-Celik, Berrin Aktekin, Canan Aykut-Bingöl:
A Bayesian change point model for epileptic seizure detection. SIU 2017: 1-4 - 2016
- [c2]Baris Kurt, Çagatay Yildiz, Taha Yusuf Ceritli, Mehmet Yamac, Murat Semerci, Bülent Sankur, Ali Taylan Cemgil:
A probabilistic SIP network simulation system. SIU 2016: 1049-1052 - [c1]Çagatay Yildiz, Taha Yusuf Ceritli, Baris Kurt, Bülent Sankur, Ali Taylan Cemgil:
Attack detection in VOIP networks using Bayesian multiple change-point models. SIU 2016: 1301-1304
Informal and Other Publications
- 2024
- [i10]Çagatay Yildiz, Nishaanth Kanna Ravichandran, Prishruit Punia, Matthias Bethge, Beyza Ermis:
Investigating Continual Pretraining in Large Language Models: Insights and Implications. CoRR abs/2402.17400 (2024) - 2023
- [i9]Ilze Amanda Auzina, Çagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves:
Invariant Neural Ordinary Differential Equations. CoRR abs/2302.13262 (2023) - [i8]Sebastian Dziadzio, Çagatay Yildiz, Gido M. van de Ven, Tomasz Trzcinski, Tinne Tuytelaars, Matthias Bethge:
Disentangled Continual Learning: Separating Memory Edits from Model Updates. CoRR abs/2312.16731 (2023) - 2022
- [i7]Çagatay Yildiz, Melih Kandemir, Barbara Rakitsch:
Learning Interacting Dynamical Systems with Latent Gaussian Process ODEs. CoRR abs/2205.11894 (2022) - [i6]Valerii Iakovlev, Çagatay Yildiz, Markus Heinonen, Harri Lähdesmäki:
Latent Neural ODEs with Sparse Bayesian Multiple Shooting. CoRR abs/2210.03466 (2022) - 2021
- [i5]Çagatay Yildiz, Markus Heinonen, Harri Lähdesmäki:
Continuous-Time Model-Based Reinforcement Learning. CoRR abs/2102.04764 (2021) - [i4]Pashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen:
Bayesian inference of ODEs with Gaussian processes. CoRR abs/2106.10905 (2021) - 2019
- [i3]Çagatay Yildiz, Markus Heinonen, Harri Lähdesmäki:
ODE$^2$VAE: Deep generative second order ODEs with Bayesian neural networks. CoRR abs/1905.10994 (2019) - 2018
- [i2]Umut Simsekli, Çagatay Yildiz, Thanh Huy Nguyen, Gaël Richard, A. Taylan Cemgil:
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization. CoRR abs/1806.02617 (2018) - [i1]Çagatay Yildiz, Markus Heinonen, Jukka Intosalmi, Henrik Mannerström, Harri Lähdesmäki:
Learning Stochastic Differential Equations With Gaussian Processes Without Gradient Matching. CoRR abs/1807.05748 (2018)
Coauthor Index
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