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Deep Learning | Postdoc, Max Planck Institute | PhD, University of Oxford | Prev. at DeepMind, Mila, and The New York Times.
KAN-Tutorial. Understanding Kolmogorov-Arnold Networks: A Tutorial Series on KAN using Toy Examples
207Hybrid-learn2branch. Hybrid Models for Learning to Branch (NeurIPS 2020)
50time_series_forecasting_tutorial. Tutorial on time series forecasting methods: from classical to llm-based approaches
36U.S-Presidential-Speeches. Textual Analysis of speeches using Google's Word2Vec Model
31covid_p2p_simulation. Simulator for COVID-19 spread
6DQN-SAT. DQN agent for SAT Solving
5ml_resources. Teaching resources for machine learning
3physics_duality. Machine Learning Approach to Duality in Statistical Physics (ICML 2025)
2GibbsSampler. GibbsSampler for MIxture Models
2AudioAge. Transferring audio features to build models for rare conditions with scarce data
1BHLDA. Body-Headline LDA : Concept of MicroLevel LDA
1lookback-learn2branch. Lookback for Learning to Branch (TMLR 2022)
1accessing-research-data. Course Assignments: Accessing Research Data | Oxford Internet Institute 2022
1Coding4Fun. Basic data structures and their application
1awesome-kan. A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.
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