IGDA: Interactive Graph Discovery through Large Language Model Agents.
CoRR, February, 2025
Adapting Language Models via Token Translation.
CoRR, 2024
Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology.
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CoRR, 2024
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine.
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CoRR, 2023
Considerations for data acquisition and modeling strategies: Mitosis detection in computational pathology.
Proceedings of the Medical Imaging with Deep Learning, 2023
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport.
CoRR, 2022
Interpretable Distribution Shift Detection using Optimal Transport.
CoRR, 2022
Rapid Model Architecture Adaption for Meta-Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
LANA: Latency Aware Network Acceleration.
Proceedings of the Computer Vision - ECCV 2022, 2022
On Hard Episodes in Meta-Learning.
CoRR, 2021
HANT: Hardware-Aware Network Transformation.
CoRR, 2021
Dataset Dynamics via Gradient Flows in Probability Space.
Proceedings of the 38th International Conference on Machine Learning, 2021
Initialization and Regularization of Factorized Neural Layers.
Proceedings of the 9th International Conference on Learning Representations, 2021
Gradient Flows in Dataset Space.
CoRR, 2020
Model-specific Data Subsampling with Influence Functions.
CoRR, 2020
Geometric Dataset Distances via Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Differentiable Feature Selection by Discrete Relaxation.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Feature Gradients: Scalable Feature Selection via Discrete Relaxation.
CoRR, 2019
Probabilistic Neural Architecture Search.
CoRR, 2019
Model Compression with Generative Adversarial Networks.
CoRR, 2018
Probabilistic Matrix Factorization for Automated Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Gaussian Process Prior Variational Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Flexible Modeling of Genetic Effects on Function-Valued Traits.
J. Comput. Biol., 2017
Flexible Modelling of Genetic Effects on Function-Valued Traits.
Proceedings of the Research in Computational Molecular Biology - 20th Annual Conference, 2016
Probabilistic latent variable models in statistical genomics.
PhD thesis, 2015
Detecting regulatory gene-environment interactions with unmeasured environmental factors.
Bioinform., 2013
Gaussian Processes for Big Data.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013
Joint Modelling of Confounding Factors and Prominent Genetic Regulators Provides Increased Accuracy in Genetical Genomics Studies.
PLoS Comput. Biol., 2012
Intrusion Detection via Artificial Immune System: a Performance-based Approach.
Proceedings of the Biologically-Inspired Collaborative Computing, 2008