Publications

Wenlin Chen*, Julien Horwood*, Juyeon Heo, José Miguel Hernández-Lobato (2023). Leveraging Task Structures for Improved Identifiability in Neural Network Representations. ICML 2023 SCIS Workshop.

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Wenlin Chen, Hong Ge (2023). Neural Characteristic Activation Value Analysis for Improved ReLU Network Feature Learning. arXiv preprint 2305.15912.

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Wenlin Chen, Austin Tripp, José Miguel Hernández-Lobato (2023). Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction. ICLR 2023.

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Wenlin Chen, Samuel Horváth, Peter Richtárik (2022). Optimal Client Sampling for Federated Learning. TMLR 2022.

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Austin Tripp, Wenlin Chen, José Miguel Hernández-Lobato (2022). An Evaluation Framework for the Objective Functions of De Novo Drug Design Benchmarks. ICLR 2022 MLDD Workshop.

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Wenlin Chen (2021). Causal Representation Learning for Latent Space Optimization. MPhil Thesis, University of Cambridge.

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Andrew Webb, Charles Reynolds, Wenlin Chen, Henry Reeve, Dan Iliescu, Mikel Luján, Gavin Brown (2020). To Ensemble or Not Ensemble: When Does End-to-End Training Fail?. ECML 2020.

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