This page provides a curated collection of high-quality learning resources across mathematics, computer science, machine learning, financial mathematics, and related disciplines. The resources include recommended textbooks, lecture notes, research papers, online courses, software tools, programming resources, and reference materials that I have found valuable for learning, teaching, and research. This collection will continue to grow as new topics and resources are added over time.
Mathematics (View Page)
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Resources covering pure and applied mathematics, including linear algebra, real analysis, graph theory, differential equations, numerical analysis, optimization, probability, and related topics.
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Computer Science (View Page)
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Resources on programming, data structures, algorithms, theory of computation, operating systems, and computational complexity.
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Arithmetic Circuit Lower Bounds via Elusive Maps: Explicit Constructions and New Approaches [Slides]
Arithmetic Circuit Lower Bounds via Explicit Construction of Elusive Maps [Slides]
Half Integrality of Minimum Vertex Cover and Nemhauser - Trotter Theorem [Slides]
Homomorphisms to prove regularity/non-regularity of languages. [Slides]
Machine Learning & Artificial Intelligence (View Page)
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Resources covering machine learning, deep learning, scientific machine learning, neural networks, PINNs, optimization, and AI.
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Financial Mathematics (View Page)
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Resources on derivatives, option pricing, computational finance, stochastic processes, numerical methods, and quantitative finance.
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Time Series & Econometrics (View Page)
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Resources on forecasting, volatility modelling, causality, structural breaks, econometrics, and financial time series.
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Samadder, S., & Sahoo, S. (2023). A Study on Trend Pattern, Integration and Causality Between Crude Oil Prices, British & American Currency Exchange Rates with Respect to Indian Rupee. In Recent Trends in Science – Platinum Jubilee Series, pp. 401–421. Walnut Publication. [Link]
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Programming & Software (View Page)
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Resources for Python, C, MATLAB, LaTeX, Git, Linux, and scientific computing.
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