8 citations · 18 across the 5 of their papers we have counts for
6 papers
AI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions
Raul Jimenez, Boris Bolliet, Francisco Villaescusa-Navarro +7
Agentic artificial intelligence (AI) systems are beginning to assist, accelerate, and partially automate scientific discovery, performing tasks that span literature synthesis, code…
Causal machine learning for single-cell genomics
Alejandro Tejada-Lapuerta, Paul Bertin, Stefan Bauer +3
Advances in single-cell omics allow for unprecedented insights into the transcription profiles of individual cells. When combined with large-scale perturbation screens, through whi…
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity
Hananeh Aliee, Ferdinand Kapl, Soroor Hediyeh-Zadeh +1
This paper presents a novel approach that leverages domain variability to learn representations that are conditionally invariant to unwanted variability or distractors. Our approac…
Sparsity in Continuous-Depth Neural Networks
Hananeh Aliee, Till Richter, Mikhail Solonin +3
Neural Ordinary Differential Equations (NODEs) have proven successful in learning dynamical systems in terms of accurately recovering the observed trajectories. While different typ…
Beyond Predictions in Neural ODEs: Identification and Interventions
Hananeh Aliee, Fabian J. Theis, Niki Kilbertus
Spurred by tremendous success in pattern matching and prediction tasks, researchers increasingly resort to machine learning to aid original scientific discovery. Given large amount…
Towards Cross-layer Reliability Analysis of Transient and Permanent Faults
Hananeh Aliee, Liang Chen, Mojtaba Ebrahimi +3
Due to the increasing complexity of Multi-Processor Systems on Chip (MPSoCs), system-level design methodologies have got a lot of attention in recent years. However, the significan…