Timeline
Recent events in my timeline
06.2025 Reviewing for GSI (Geometric Science of Information) 2025 — the biennial flagship conference in Information Geometry, with involvement (as author/reviewer) dating back to 2017.
06.2025 New article published: “A geometric modeling of Occam’s razor in deep learning”, Sun and Nielsen, Information Geometry, Special Issue: Half a Century of Information Geometry, Part 2, Springer, 2025. (arxiv) (open access link) 
05.2025: My preprint “Deterministic Bounds and Random Estimates of Metric Tensors on Neuromanifolds” provides a computationally efficient method to estimate the Fisher information for deep neural networks, with a new analysis.
05.2025: Serving as an area chair of NeurIPS 2025.
10.2024: “Tradeoffs of Diagonal Fisher Information Matrix Estimators”, Soen and Sun. NeurIPS 2024 (to appear).
10.2024: Serving as an Area Chair (AC) for ICLR 2025.
07.2024: “Information Theory in Emerging Machine Learning Techniques”, a special issue of Entropy (MDPI) where I serve as the guest editor, is open for submission (deadline March 2025).
02.2024: “Tradeoffs of Diagonal Fisher Information Matrix Estimators”, Soen and Sun. Our recent follow-up of “On the Variance of the Fisher Information for Deep Learning” at NeurIPS 2021.
01.2024: Lecturing at AMSI summer school 2024.
01.2024: Serving as an Area Chair in ICLR 2024.
12.2023: Updated article “A Geometric Modeling of Occam’s Razor in Deep Learning”, Sun and Nielsen. Interested readers are invited to follow it on ResearchGate.
07.2022: Outstanding reviewer (Top 10%) of ICML 2022.
07.2022: “Secure Quantized Training for Deep Learning”, Keller and Sun, ICML, 2022. (proceedings) (arxiv)
07.2022: One of the “top reviewers” for UAI 2022.
03.2022: “Local Measurements of Non-linear Embeddings with Information Geometry”, Geometry and Statistics, Vol. 46 of Handbook of Statistics, Ed. Frank Nielsen, Arni Srinivasa Rao, C.R. Rao, 2022. (book) (arxiv)
02.2022: One of the “top reviewers” for AISTATS 2022
12.2020: Keynote “Information Geometry for Data Geometry through Pullbacks” (video) (slides) in Neurips 2020 workshop on Deep Learning through Information Geometry
11.2020: Book chapter: “Chain Rule Optimal Transport” (arxiv) in Progress in Information Geometry Theory and Applications, F. Nielsen Ed., Springer, 2021.
2020: D61 postdoc openning (deadline soon!) on Machine Learning and Artificial Intelligence: Decision Making
2020: TNNLS article: q-Neurons: Neuron Activations Based on Stochastic Jackson’s Derivative Operators
2020: PC service in early 2020: ICML, IJCAI-PRICAI, UAI
2019: You are welcome to visit our poster “Information Geometric Set Embeddings (IGSE): From Sets to Distributions” in the NeurIPS-19 workshop of Sets and Partitions.
2019: I served as a reviewer/PC member of ICLR (outstanding reviewer), AISTATS, ICML, IJCAI, GSI, UAI, NeurIPS (one of the “top reviewers”) and did emergency reviews for ICCV, AAAI, etc.
2019: Check our latest work on Lightlike Neuromanifolds, Occam’s Razor and Deep Learning which explains generalization of deep learning using geometric tools from general relativity.
2019: I am attending UAI (July 22-25 2019) to present our recent work on Fisher-Bures Adversary Graph Convolutional Networks.