Theofanis Karaletsos

According to our database, Theofanis Karaletsos authored at least 28 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Compositional Deep Probabilistic Models of DNA-Encoded Libraries.

Benson Chen, Mohammad M. Sultan, Theofanis Karaletsos

J. Chem. Inf. Model., February, 2024

Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.

Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang

CoRR, 2024

2023

DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries.

Kirill Shmilovich, Benson Chen, Theofanis Karaletsos, Mohammad M. Sultan

J. Chem. Inf. Model., May, 2023

Channel Vision Transformers: An Image Is Worth C x 16 x 16 Words.

Yujia Bao, Srinivasan Sivanandan, Theofanis Karaletsos

CoRR, 2023

Contextual Vision Transformers for Robust Representation Learning.

Yujia Bao, Theofanis Karaletsos

CoRR, 2023

Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder.

Michael Bereket, Theofanis Karaletsos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Black-box coreset variational inference.

Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

TyXe: Pyro-based Bayesian neural nets for Pytorch.

Hippolyt Ritter, Theofanis Karaletsos

Proceedings of Machine Learning and Systems 2022, 2022

2021

Localized Uncertainty Attacks.

Ousmane Amadou Dia, Theofanis Karaletsos, Caner Hazirbas, Cristian Canton-Ferrer, Ilknur Kaynar Kabul, Erik Meijer

CoRR, 2021

Stochastic Aggregation in Graph Neural Networks.

Yuanqing Wang, Theofanis Karaletsos

CoRR, 2021

Variational Auto-Regressive Gaussian Processes for Continual Learning.

Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights.

Theofanis Karaletsos, Thang D. Bui

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalized Hidden Parameter MDPs: Transferable Model-Based RL in a Handful of Trials.

Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Pyro: Deep Universal Probabilistic Programming.

Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul A. Szerlip, Paul Horsfall, Noah D. Goodman

J. Mach. Learn. Res., 2019

Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference.

Xinyu Hu, Paul A. Szerlip, Theofanis Karaletsos, Rohit Singh

CoRR, 2019

Pathwise Derivatives for Multivariate Distributions.

Martin Jankowiak, Theofanis Karaletsos

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Efficient transfer learning and online adaptation with latent variable models for continuous control.

Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos

CoRR, 2018

Probabilistic Meta-Representations Of Neural Networks.

Theofanis Karaletsos, Peter Dayan, Zoubin Ghahramani

CoRR, 2018

Likelihood-free inference with emulator networks.

Jan-Matthis Lueckmann, Giacomo Bassetto, Theofanis Karaletsos, Jakob H. Macke

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2018

2017

RiboDiff: detecting changes of mRNA translation efficiency from ribosome footprints.

Yi Zhong, Theofanis Karaletsos, Philipp Drewe, Vipin T. Sreedharan, David Kuo, Kamini Singh, Hans-Guido Wendel, Gunnar Rätsch

Bioinform., 2017

Conditional Similarity Networks.

Andreas Veit, Serge J. Belongie, Theofanis Karaletsos

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Disentangling Nonlinear Perceptual Embeddings With Multi-Query Triplet Networks.

Andreas Veit, Serge J. Belongie, Theofanis Karaletsos

CoRR, 2016

When crowds hold privileges: Bayesian unsupervised representation learning with oracle constraints.

Theofanis Karaletsos, Serge J. Belongie, Gunnar Rätsch

Proceedings of the 4th International Conference on Learning Representations, 2016

Adversarial Message Passing For Graphical Models.

Theofanis Karaletsos

CoRR, 2016

Knowledge Transfer with Medical Language Embeddings.

Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch

CoRR, 2016

A Generative Model of Words and Relationships from Multiple Sources.

Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2013

An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes.

Katherine Redfield Chan, Xinghua Lou, Theofanis Karaletsos, Christopher Crosbie, Stuart M. Gardos, David Artz, Gunnar Rätsch

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

2012

ShapePheno: unsupervised extraction of shape phenotypes from biological image collections.

Theofanis Karaletsos, Oliver Stegle, Christine Dreyer, John M. Winn, Karsten M. Borgwardt

Bioinform., 2012