Michalis K. Titsias

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

Venues

Active years

2000–2025

Best venue rank

Where they publish

Papers

24 indexed papers, newest first.

Year	Venue	Title	Authors
2025	ICML	Learning-Order Autoregressive Models with Application to Molecular Graph Generation.	Zhe Wang, Jiaxin Shi, Nicolas Heess, Arthur Gretton, Michalis K. Titsias
2025	ICML	New Bounds for Sparse Variational Gaussian Processes.	Michalis K. Titsias
2024	ICLR	Kalman Filter for Online Classification of Non-Stationary Data.	Michalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jrg Bornschein
2022	AISTATS	Double Control Variates for Gradient Estimation in Discrete Latent Variable Models.	Michalis K. Titsias, Jiaxin Shi
2022	ICLR	Information-theoretic Online Memory Selection for Continual Learning.	Shengyang Sun, Daniele Calandriello, Huiyi Hu, Ang Li, Michalis K. Titsias
2021	UAI	Unbiased gradient estimation for variational auto-encoders using coupled Markov chains.	Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet
2021	UAI	Information theoretic meta learning with Gaussian processes.	Michalis K. Titsias, Francisco J. R. Ruiz, Sotirios Nikoloutsopoulos, Alexandre Galashov
2020	AISTATS	Sparse Orthogonal Variational Inference for Gaussian Processes.	Jiaxin Shi, Michalis K. Titsias, Andriy Mnih
2020	ICLR	Functional Regularisation for Continual Learning with Gaussian Processes.	Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu, Yee Whye Teh
2019	AISTATS	Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models.	Kaspar Mrtens, Michalis K. Titsias, Christopher Yau
2019	AISTATS	Unbiased Implicit Variational Inference.	Michalis K. Titsias, Francisco J. R. Ruiz
2019	ICML	A Contrastive Divergence for Combining Variational Inference and MCMC.	Francisco J. R. Ruiz, Michalis K. Titsias
2018	ICML	Augment and Reduce: Stochastic Inference for Large Categorical Distributions.	Francisco J. R. Ruiz, Michalis K. Titsias, Adji B. Dieng, David M. Blei
2017	ICML	Bayesian Boolean Matrix Factorisation.	Tammo Rukat, Christopher C. Holmes, Michalis K. Titsias, Christopher Yau
2016	MOBIHOC	First learn then earn: optimizing mobile crowdsensing campaigns through data-driven user profiling.	Merkourios Karaliopoulos, Iordanis Koutsopoulos, Michalis K. Titsias
2016	UAI	Overdispersed Black-Box Variational Inference.	Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei
2014	ICML	Doubly Stochastic Variational Bayes for non-Conjugate Inference.	Michalis K. Titsias, Miguel Lzaro-Gredilla
2013	IGARSS	Estimation of vegetation chlorophyll content with Variational Heteroscedastic Gaussian Processes.	Miguel Lzaro-Gredilla, Michalis K. Titsias, Jochem Verrelst, Gustavo Camps-Valls
2012	ICML	Manifold Relevance Determination.	Andreas C. Damianou, Carl Henrik Ek, Michalis K. Titsias, Neil D. Lawrence
2011	ICML	Variational Heteroscedastic Gaussian Process Regression.	Miguel Lzaro-Gredilla, Michalis K. Titsias
2009	WAW	Web Page Rank Prediction with PCA and EM Clustering.	Polyxeni Zacharouli, Michalis K. Titsias, Michalis Vazirgiannis
2005	BMVC	Fast Learning of Sprites using Invariant Features.	Moray Allan, Michalis K. Titsias, Christopher K. I. Williams
2004	CVPR	Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video.	Michalis K. Titsias, Christopher K. I. Williams
2000	IJCNN	A Probabilistic RBF Network for Classification.	Michalis K. Titsias, Aristidis Likas