Publications

Full list. Also on Google Scholar. ✶ co-senior   * equal contribution

Domains
Topics
AI for Science
Virtual Cell & Cellular Biology
Building the Virtual Cell with Artificial Intelligence
C. Bunne*, Y. Roohani*, Y. Rosen*, ..., T. Karaletsos✶, A. Regev✶, E. Lundberg✶, J. Leskovec✶, S.R. Quake✶
Cell, 2024  * equal contribution  ✶ co-seniorpaperarXiv '24
A Cross-Species Generative Cell Atlas Across 1.5 Billion Years of Evolution: The TranscriptFormer Single-cell Model
J.D. Pearce, S.E. Simmonds, G. Mahmoudabadi, L. Krishnan, G. Palla, A. Istrate, A. Tarashansky, B. Nelson, O. Valenzuela, D. Li, S.R. Quake✶, T. Karaletsos✶
bioRxiv, 2025  ✶ co-seniorbioRxiv '25
Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models
G. Palla, S. Babu, P. Dibaeinia, J.D. Pearce, D. Li, A.A. Khan, T. Karaletsos✶, J.M. Tomczak✶
NeurIPS 2025 Workshop AI4D3  ✶ co-seniorarXiv '25
GREmLN: A Cellular Graph Structure Aware Transcriptomics Foundation Model
M. Zhang, V. Swamy, R. Cassius, L. Dupire, C. Kanatsoulis, E. Paull, M. AlQuraishi, T. Karaletsos, A. Califano
bioRxiv, 2025bioRxiv '25
SubCell: Proteome-Aware Vision Foundation Models for Microscopy Capture Single-Cell Biology
A. Gupta, Z. Wefers, K. Kahnert, J.N. Hansen, M.K. Misra, W. Leineweber, A. Cesnik, D. Lu, U. Axelsson, F. Balllosera Navarro, R.B. Altman, T. Karaletsos, E. Lundberg
bioRxiv, 2024bioRxiv '24
Learning Explicit Single-Cell Dynamics Using ODE Representations
J. von Bassewitz, A. Pervez, M. Fumero, M. Robinson, T. Karaletsos, F. Locatello
ICLR 2026arXiv '25
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder
M. Bereket, T. Karaletsos
NeurIPS 2023paperarXiv '23
scGenePT: Is Language All You Need for Modeling Single-Cell Perturbations?
A. Istrate, D. Li, T. Karaletsos
bioRxiv, 2024bioRxiv '24
VariantFormer: A Hierarchical Transformer Integrating DNA Sequences with Genetic Variations and Regulatory Landscapes for Personalized Gene Expression Prediction
S. Ghosal, Y. Barhomi, T. Ganapathi, A. Krystosik, L. Krishnan, S. Guntury, D. Li, F.P. Casale, T. Karaletsos
bioRxiv, 2025bioRxiv '25
RiboDiff: Detecting Changes of mRNA Translation Efficiency from Ribosome Footprints
Y. Zhong, T. Karaletsos, P. Drewe, V.T. Sreedharan, D. Kuo, K. Singh, H. Wendel, G. Rätsch
Bioinformatics, Vol. 33, No. 1, 2017paperbioRxiv '15
A Roadmap for Predictive Human Immunology
A.A. Khan, J. Perera, J. Zou, ..., T. Karaletsos, et al.
arXiv, 2025arXiv '25
MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging
B. Demirel, M. Fumero, T. Karaletsos, F. Locatello
arXiv, 2025arXiv '25
Species-Specific Small Models for Cell Type Classification Approach the Performance of Large Single Cell Foundation Models
G. Mahmoudabadi, L. Krishnan, T. Ganapathi, J.D. Pearce, S.R. Quake, T. Karaletsos
bioRxiv, 2026bioRxiv '26
A Path Towards AI-Scale, Interoperable Biological Data
B. Aevermann, A. Califano, ..., T. Karaletsos, ..., A.J. Carr
arXiv, 2025arXiv '25
AI: A Transformative Opportunity in Cell Biology
A. Carr, J. Cool, T. Karaletsos, D. Li, A.R. Lowe, S. Otte, S.L. Schmid
Molecular Biology of the Cell, 2024paper
Deep Learning Analysis on Images of iPSC-derived Motor Neurons Carrying fALS-Genetics Reveals Disease-Relevant Phenotypes
R. Atmaramani, T. Dreossi, ..., T. Karaletsos, ..., S. Sances
bioRxiv, 2024bioRxiv '24
ShapePheno: Unsupervised Extraction of Shape Phenotypes from Biological Image Collections
T. Karaletsos, O. Stegle, C. Dreyer, J.M. Winn, K.M. Borgwardt
Bioinformatics, Vol. 28, No. 7, 2012paper
JigPheno: Semantic Feature Extraction From Biological Images
T. Karaletsos, O. Stegle, J.M. Winn, K.M. Borgwardt
NIPS Workshop on Machine Learning in Computational Biology, 2010 (oral)talk
Genetics
BayesRVAT Enhances Rare-Variant Association Testing through Bayesian Aggregation of Functional Annotations
A. Nappi, L. Shilova, T. Karaletsos, N. Cai, F.P. Casale
Genome Research, 2025paper
An Allelic-Series Rare-Variant Association Test for Candidate-Gene Discovery
Z.R. McCaw, C. O'Dushlaine, H. Somineni, M. Bereket, C. Klein, T. Karaletsos, F.P. Casale, D. Koller, T.W. Soare
The American Journal of Human Genetics, 2023paperbioRxiv '22
EmbedGEM: A Framework to Evaluate the Utility of Embeddings for Genetic Discovery
S. Mukherjee, Z.R. McCaw, ..., T. Karaletsos, et al.
Bioinformatics Advances, 2024paper
Pitfalls in Performing Genome-Wide Association Studies on Ratio Traits
Z.R. McCaw, R. Dey, H. Somineni, D. Amar, S. Mukherjee, C. Sandor, T. Karaletsos, D. Koller, H. Aschard, G.D. Smith, D.G. MacArthur, C. O'Dushlaine, T.W. Soare
Human Genetics and Genomics Advances, 2025paper
Clinical & Healthcare AI
Knowledge Transfer with Medical Language Embeddings
S.L. Hyland, T. Karaletsos, G. Rätsch
SDM Workshop on Data Mining for Medicine and Healthcare / NIPS ML in Healthcare, 2015arXiv '16
Probabilistic Disease Progression Models For Retrospective Analysis Of Cancer Health Records
T. Karaletsos, S. Stark, G. Rätsch
NIPS Workshop on Machine Learning in Healthcare, 2015
Poisson Matrix Factorization For Joint Modeling Of Genetics and Medical Text
M. Fernandez, T. Karaletsos, J. Vogt, S. Hyland, G. Rätsch, F. Perez-Cruz
NIPS Workshop on Machine Learning in Healthcare, 2015
Towards an Integrated Dynamic Model of Temporal Structure of Clinical Textnotes and Interactions with Genetic Profiles
T. Karaletsos, X. Lou, K.R. Chan, C. Crosbie, G. Rätsch
NIPS Workshop on Machine Learning for Clinical Data Analysis in Healthcare, 2013
An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes
K.R. Chan, X. Lou, T. Karaletsos, C. Crosbie, S.M. Gardos, D. Artz, G. Rätsch
ICDM Workshops, 2013
Scientific Reasoning
rbio1: Training Scientific Reasoning LLMs with Biological World Models as Soft Verifiers
A. Istrate, F. Milletari, F. Castrotorres, J.M. Tomczak, M. Torkar, D. Li, T. Karaletsos
NeurIPS 2025 Workshop AI4D3bioRxiv '25
How Well Do LLMs Understand Drug Mechanisms? A Knowledge + Reasoning Evaluation Dataset
S. Mohan, T. Karaletsos
FLLM 2025arXiv '25
Drug Discovery & Molecular AI
Compositional Deep Probabilistic Models of DNA-Encoded Libraries
B. Chen, M.M. Sultan, T. Karaletsos
Journal of Chemical Information and Modeling, 2024paperarXiv '23
DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries
K. Shmilovich, B. Chen, T. Karaletsos, M.M. Sultan
Journal of Chemical Information and Modeling, 2023paperarXiv '22
Bayesian Active Drug Discovery
Y. Wang, M. Nguyen, M. Retchin, J.D. Chodera, T. Karaletsos
Real-World ML Workshop, ICML 2020paper
Probabilistic & Bayesian ML / Generative AI
Generative Models & Diffusion
Calibrated Test-Time Guidance for Bayesian Inference
D. Geyfman, F. Draxler, J. Groeneveld, H. Lee, T. Karaletsos, S. Mandt
arXiv, 2026arXiv '26
Variational Control for Guidance in Diffusion Models
K. Pandey, F. Marouf Sofian, F. Draxler, T. Karaletsos, S. Mandt
ICML 2025paperarXiv '25
Likelihood-Free Inference with Emulator Networks
J. Lueckmann, G. Bassetto, T. Karaletsos, J.H. Macke
Symposium on Advances in Approximate Bayesian Inference, 2018paperarXiv '18
Bayesian Unsupervised Representation Learning with Oracle Constraints
T. Karaletsos, S. Belongie, G. Rätsch
ICLR 2016arXiv '15
Bayesian Deep Learning & Uncertainty
Position: Agentic AI Systems Should Be Making Bayes-Consistent Decisions
T. Papamarkou, P. Alquier, ..., T. Karaletsos, et al.
SSRN preprint, 2026SSRN
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
T. Papamarkou, M. Skoularidou, K. Palla, ..., T. Karaletsos, et al.
ICML 2024paperarXiv '24
Black-Box Coreset Variational Inference
D. Manousakas✶, H. Ritter✶, T. Karaletsos
NeurIPS 2022  ✶ equal contributionpaperarXiv '22
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
T. Karaletsos✶, T.D. Bui✶
NeurIPS 2020  ✶ equal contributionpaperarXiv '20
Probabilistic Meta-Representations of Neural Networks
T. Karaletsos, P. Dayan, Z. Ghahramani
UAI Workshop on Uncertainty in Deep Learning, 2018arXiv '18
Variational Inference & Probabilistic Methods
Variational Auto-Regressive Gaussian Processes for Continual Learning
S. Kapoor, T. Karaletsos, T.D. Bui
ICML 2021paperarXiv '20
Pathwise Derivatives for Multivariate Distributions
M. Jankowiak, T. Karaletsos
AISTATS 2019paperarXiv '18
Adversarial Message Passing for Graphical Models
T. Karaletsos
NIPS Workshop on Advances in Approximate Bayesian Inference, 2016arXiv '16
Automatic Relevance Determination for Deep Generative Models
T. Karaletsos, G. Rätsch
arXiv, 2015arXiv '15
Probabilistic Programming
TyXe: Pyro-based Bayesian Neural Networks for PyTorch
H. Ritter, T. Karaletsos
MLSys 2022paperarXiv '21
Pyro: Deep Universal Probabilistic Programming
E. Bingham, J.P. Chen, M. Jankowiak, N. Pradhan, T. Karaletsos, et al.
Journal of Machine Learning Research, 2019paperwebsitearXiv '18
Deep Learning, Representation Learning & RL
Language Models & Sequence Modeling
Parallel Token Prediction for Language Models
F. Draxler, J. Will, F. Marouf Sofian, T. Karaletsos, S. Singh, S. Mandt
ICLR 2026paperarXiv '25
Transformers for Mixed-type Event Sequences
F. Draxler, Y. Meng, K. Nelson, L. Laskowski, Y. Yang, T. Karaletsos, S. Mandt
NeurIPS 2025 (Spotlight)paper
A Generative Model of Words and Relationships from Multiple Sources
S.L. Hyland, T. Karaletsos, G. Rätsch
AAAI 2016paperarXiv '15
Vision & Representation Learning
Statistical and Structural Identifiability in Representation Learning
W. Nelson, M. Fumero, T. Karaletsos, F. Locatello
ICLR 2026paperarXiv '26
Channel Vision Transformers: An Image Is Worth 1 × 16 × 16 Words
Y. Bao, S. Sivanandan, T. Karaletsos
ICLR 2024paperarXiv '23
Adjusting Pretrained Backbones for Performativity
B. Demirel, L. Kong, K. Zhang, T. Karaletsos, C. Mendler-Dünner, F. Locatello
arXiv, 2024arXiv '24
Contextual Vision Transformers for Robust Representation Learning
Y. Bao, T. Karaletsos
arXiv, 2023arXiv '23
Stochastic Aggregation in Graph Neural Networks
Y. Wang, T. Karaletsos
arXiv, 2021arXiv '21
Conditional Similarity Networks
A. Veit, S. Belongie, T. Karaletsos
CVPR 2017paperarXiv '16
Reinforcement Learning & Transfer
Generalized Hidden Parameter MDPs: Transferable Model-Based RL in a Handful of Trials
C. Perez, F. Such, T. Karaletsos
AAAI 2020 (oral)paperarXiv '20
Efficient Transfer Learning and Online Adaptation with Latent Variable Models for Continuous Control
C. Perez, F. Such, T. Karaletsos
NeurIPS Workshop on Continual Learning, 2018arXiv '18
Patents
Synthon Embeddings for Modeling DNA-Encoded Libraries
B. Chen, M.M. Sultan, T. Karaletsos
US20250131979A1, Insitro, 2025patent
Predicting Cellular Responses to Perturbations
T. Karaletsos, M. Bereket
WO2024238984A3, Insitro, 2025patent
Molecular Docking-Enabled Modeling of DNA-Encoded Libraries
M.M. Sultan, B. Chen, K. Shmilovich, T. Karaletsos
WO2024118605A1, Insitro, 2024patent
Intelligent Regularization of Neural Network Architectures
Z. Ghahramani, D. Bemis, T. Karaletsos
US20240013049A1, Uber Technologies, 2024patent
Model Based Reinforcement Learning Based on Generalized Hidden Parameter Markov Decision Processes
C. Perez, F. Such, T. Karaletsos
US20200372410A1, Uber Technologies, 2020patent
Representations of Units in Neural Networks
T. Karaletsos, P. Dayan, Z. Ghahramani
US20190286970A1, Uber Technologies, 2019patent
Event Detection Using Sensor Data
N.P. Volk, T. Karaletsos, U. Madhow, J.B. Yosinski, T.R. Sumers
US20190205785A1, Uber Technologies, 2019patent