Kaspar Märtens

19 papers A* 2A 3Journal 13Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MechPert: Mechanistic Consensus as an Inductive Bias for Unseen Perturbation Prediction. CoRR Marc Boubnovski Martell, Josefa Lia Stoisser, Lawrence Phillips, Aditya Misra, Robert Kitchen, Jesper Ferkinghoff-Borg, Jialin Yu, Philip Torr, Kaspar Märtens
2025	J	`jnl`	Modeling Gene Expression Distributional Shifts for Unseen Genetic Perturbations. CoRR Kalyan Ramakrishnan, Jonathan G. Hedley, Sisi Qu, Puneet K. Dokania, Philip H. S. Torr, Cesar A. Prada-Medina, Julien Fauqueur, Kaspar Märtens
2025	J	`jnl`	Query, Don't Train: Privacy-Preserving Tabular Prediction from EHR Data via SQL Queries. CoRR Josefa Lia Stoisser, Marc Boubnovski Martell, Kaspar Märtens, Lawrence Phillips, Stephen Michael Town, Rory M. Donovan-Maiye, Julien Fauqueur
2025	J	`jnl`	SynthPert: Enhancing LLM Biological Reasoning via Synthetic Reasoning Traces for Cellular Perturbation Prediction. CoRR Lawrence Phillips, Marc Boubnovski Martell, Aditya Misra, Josefa Lia Stoisser, Cesar A. Prada-Medina, Rory M. Donovan-Maiye, Kaspar Märtens
2025	J	`jnl`	Towards Agents That Know When They Don't Know: Uncertainty as a Control Signal for Structured Reasoning. CoRR Josefa Lia Stoisser, Marc Boubnovski Martell, Lawrence Phillips, Gianluca Mazzoni, Lea Mørch Harder, Philip Torr, Jesper Ferkinghoff-Borg, Kaspar Märtens, Julien Fauqueur
2025	J	`jnl`	Towards Label-Free Biological Reasoning Synthetic Dataset Creation via Uncertainty Filtering. CoRR Josefa Lia Stoisser, Lawrence Phillips, Aditya Misra, Tom A. Lamb, Philip Torr, Marc Boubnovski Martell, Julien Fauqueur, Kaspar Märtens
2024	J	`jnl`	Disentangling shared and private latent factors in multimodal Variational Autoencoders. CoRR Kaspar Märtens, Christopher Yau
2023	A*	`conf`	Deep Stochastic Processes via Functional Markov Transition Operators. NeurIPS Jin Xu, Emilien Dupont, Kaspar Märtens, Thomas Rainforth, Yee Whye Teh
2023	J	`jnl`	Deep Stochastic Processes via Functional Markov Transition Operators. CoRR Jin Xu, Emilien Dupont, Kaspar Märtens, Tom Rainforth, Yee Whye Teh
2023	—	`conf`	Disentangling shared and private latent factors in multimodal Variational Autoencoders. MLCB Kaspar Märtens, Christopher Yau
2023	J	`jnl`	Rarity: discovering rare cell populations from single-cell imaging data. Bioinform. Kaspar Märtens, Michele Bortolomeazzi, Lucia Montorsi, Jo Spencer, Francesca D. Ciccarelli, Christopher Yau
2020	A	`conf`	BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders. AISTATS Kaspar Märtens, Christopher Yau
2020	J	`jnl`	BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders. CoRR Kaspar Märtens, Christopher Yau
2020	A	`conf`	Neural Decomposition: Functional ANOVA with Variational Autoencoders. AISTATS Kaspar Märtens, Christopher Yau
2020	J	`jnl`	Neural Decomposition: Functional ANOVA with Variational Autoencoders. CoRR Kaspar Märtens, Christopher Yau
2019	A	`conf`	Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models. AISTATS Kaspar Märtens, Michalis K. Titsias, Christopher Yau
2019	A*	`conf`	Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models. ICML Kaspar Märtens, Kieran R. Campbell, Christopher Yau
2018	J	`jnl`	Covariate Gaussian Process Latent Variable Models. CoRR Kaspar Märtens, Kieran R. Campbell, Christopher Yau
2016	J	`jnl`	seqlm: an MDL based method for identifying differentially methylated regions in high density methylation array data. Bioinform. Raivo Kolde, Kaspar Märtens, Kaie Lokk, Sven Laur, Jaak Vilo