add Chen2025a

Author: michaelgutmann

_assets/Refereed.bib

@@ -1128,6 +1128,16 @@ @Article{Simkus2024a
   url       = {https://openreview.net/forum?id=lLVmIvZfry},
 }
 
+@InProceedings{Chen2025a,
+  author    = {Yanzhi Chen and Zijing Ou and Adrian Weller and Michael U Gutmann},
+  booktitle = {The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS)},
+  title     = {Neural Mutual Information Estimation with Vector Copulas},
+  year      = {2025},
+  abstract  = {Estimating mutual information (MI) is a fundamental task in data science and machine learning. Existing estimators mainly rely on either highly flexible models (e.g., neural networks), which require large amounts of data, or overly simplified models (e.g., Gaussian copula), which fail to capture complex distributions. Drawing upon recent vector copula theory, we propose a principled interpolation between these two extremes to achieve a better trade-off between complexity and capacity. Experiments on state-of-the-art synthetic benchmarks and real-world data with diverse modalities demonstrate the advantages of the proposed method.},
+  arxiv     = {https://arxiv.org/abs/2510.20968},
+  url       = {https://openreview.net/forum?id=FYbe7r0mxu},
+}
+
 @Comment{jabref-meta: databaseType:bibtex;}
 
 @Comment{jabref-meta: fileDirectory-mgutmann-zermatt:../myPapers;}

index.md

@@ -19,8 +19,8 @@ A short biography is available [here](bio/index.html).
 
 ## Recent papers
 
+* NeurIPS: Neural Mutual Information Estimation with Vector Copulas [[link]](publications/index.html#Chen2025a)
 * arXiv: CFMI: Flow Matching for Missing Data Imputation [[link]](publications/index.html#Simkus2025a)
 * arXiv: Simulation-based Bayesian inference under model misspecification [[link]](publications/index.html#Kelly2025a)
 * BioRxiv: Risk-averse optimization of genetic circuits under uncertainty [[link]](publications/index.html#Kobiela2024a)
 * TMLR: Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families [[link]](publications/index.html#Simkus2024a)
-* eLife: Designing Optimal Behavioral Experiments Using Machine Learning [[link]](publications/index.html#Valentin2023a)