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Library

Overview of books for our library

Neuroscience

  • Principles of Neural Science, by Eric R. Kandel (Editor), James H. Schwartz (Editor), Thomas M. Jessell (Editor), Steven A. Siegelbaum (Editor), A. J. Hudspeth (Editor)

  • Neuroscience by Dale Purves and George J. Augustine

  • Neuroscience: Exploring the Brain by Mark F. Bear and Barry W. Connors

Connectome

  • Handbook of Brain Connectivity (Understanding Complex Systems) by Viktor K. Jirsa (Editor), A.R. McIntosh (Editor)

  • Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior (Springer Series in Computational Neuroscience) by Jose Luis Perez Velazquez (Editor), Richard Wennberg (Editor)

Computational Neuroscience

  • Principles of Computational Modelling in Neuroscience, by David Sterratt (Author), Bruce Graham (Author), Andrew Gillies (Author)

  • Biophysics of Computation: Information Processing in Single Neurons by Christof Koch (Author)

  • Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems by Laurence F. Abbott (Author), Peter Dayan (Author)

  • Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition by Wulfram Gerstner (Author), Werner M. Kistler (Author), Richard Naud (Author), Liam Paninski (Author)

  • Spikes: Exploring the Neural Code (Computational Neuroscience) by Fred Rieke and David Warland

  • The Handbook of Brain Theory and Neural Networks (A Bradford Book) by Michael A. Arbib

  • Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience Series) by Eugene M. Izhikevich (Author), Terrence J. Sejnowski

  • Handbook of Neural Activity Measurement by Romain Brette, Alain Destexhe

  • Introduction to Theoretical Neurobiology Vol 1: Linear Cable Theory and Dendritic Structure

  • Introduction to Theoretical Neurobiology Vol 2: Nonlinear and Stochastic Theories

  • Modeling in the Neurosciences: From Biological Systems to Neuromimetic Robotics​

  • Computational Neuroscience: A Comprehensive Approach

  • Mathematics for Neuroscientist

  • Mathematical Foundations of Neuroscience

  • Waves in Neural Media: From single Neurons to Fields

  • Neural Fields: Theory and Applications

Computational Biology

  • Random Walks in Biology by Howard C. Berg

  • Biophysics: Searching for Principles by William Bialek

  • Bridging Time Scales: Molecular Simulations for the Next Decade

  • Stochastic Processes in Cell Biology

  • Mathematical Biology: I. An Introduction (Interdisciplinary Applied Mathematics) (Pt. 1) by J.D. Murray

  • Mathematical Biology II: Spatial Models and Biomedical Applications (Interdisciplinary Applied Mathematics) (v. 2) by J.D. Murray

Math

  • Fourier Analysis: An Introduction (Princeton Lectures in Analysis, Volume 1) by Elias M. Stein and Rami Shakarchi

  • Complex Analysis (Princeton Lectures in Analysis, No. 2) by Elias M. Stein and Rami Shakarchi

  • Real Analysis: Measure Theory, Integration, and Hilbert Spaces (Princeton Lectures in Analysis) (Bk. 3) by Elias M. Stein and Rami Shakarchi

  • Functional Analysis: Introduction to Further Topics in Analysis (Princeton Lectures in Analysis) (Bk. 4) by Elias M. Stein and Rami Shakarchi

  • Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, Second Edition (Studies in Nonlinearity) (Volume 1) by Steven H. Strogatz

  • Linear Algebra and Its Applications by Gilbert Strang

  • Introduction to Applied Mathematics, by Gilbert Strang

  • Differential Equations and Linear Algebra, by Gilbert Strang

Stats

  • Statistics: A Guide to the Use of Statistical Methods in the Physical Sciences by R. J. Barlow

  • All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics) by Larry Wasserman

  • All of Nonparametric Statistics (Springer Texts in Statistics) by Larry Wasserman

Bayesian

  • Bayesian Data Analysis by Andrew Gelman (Author), John B. Carlin (Author), Hal S. Stern (Author), David B. Dunson (Author), Aki Vehtari (Author), Donald B. Rubin (Author)

  • Statistical Rethinking: A Bayesian Course with Examples in R and Stan by Richard McElreath

Causal inference

  • Causality: Models, Reasoning and Inference by Judea Pearl

  • Causal Inference in Statistics: A Primer by Judea Pearl and Madelyn Glymour

  • Mostly Harmless Econometrics: An Empiricist's Companion by Joshua D. Angrist and Jörn-Steffen Pischke

Analysis

  • Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators (Wiley Series in Probability and Statistics) by Tailen Hsing and Randall Eubank

  • Analysis of Neural Data by Kass, Robert E., Eden, Uri, Brown, Emery

Machine Learning

  • Deep Learning with Python by Francois Chollet

  • Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent by Aurélien Géron

  • Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto

  • The Elements of Statistical Learning: Data Mining, Inference, and Prediction, (Springer Series in Statistics) by Trevor Hastie (Author), Robert Tibshirani (Author), Jerome Friedman (Author)

  • Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig

Complexity and Information Theory

  • Information Theory: A Tutorial Introduction Paperback by James V Stone (Author)

  • Information Theory, Inference and Learning Algorithms by David J.C. MacKay

  • Information, Physics, and Computation (Oxford Graduate Texts) by Marc Mézard and Andrea Montanari

  • The Nonlinear World: Conceptual Analysis and Phenomenology (Springer Series in Synergetics) by Yoshitsugu Oono

  • Six Degrees: The Science of a Connected Age Reprint Edition by Duncan J. Watts (Author)

  • Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life by Albert-Laszlo Barabasi (Author)

  • Complexity: A Guided Tour by Melanie Mitchell (Author)

  • Supercooperators: The Mathematics of Evolution, Altruism and Human Behaviour, (Or, Why We Need Each Other to Succeed) by M A Nowak (Author)

  • Graph Theory and Complex Networks: An Introduction by Maarten van Steen (Author)

  • Networks: An Introduction by Mark Newman (Author)

  • Dynamical Processes on Complex Networks by Alain Barrat (Author), Marc Barthélemy (Author), Alessandro Vespignani (Author)

  • Evolution of Networks: From Biological Nets to the Internet and WWW (Physics) by S. N. Dorogovtsev (Author), J.F.F. Mendes (Author)

  • Graph Spectra for Complex Networks by Piet Van Mieghem

  • The Structure of Complex Networks: Theory and Applications by Ernesto Estrada (Author)

  • Networks of the Brain (MIT Press) by Olaf Sporns (Author)

Signal Processing

  • Digital Signal Processing by Alan V. Oppenheim and Ronald W. Schafer

  • Independent Component Analysis by Aapo Hyvarinen, Erkki Oja, and Juha Karhunen

Biology

  • Life: The Science of Biology, by David E. Sadava (Author), David M. Hillis (Author), H. Craig Heller (Author), May Berenbaum (Author)

General

  • The Structure of Scientific Revolutions by Thomas S. Kuhn (Author)

  • Sync by Strogatz

Wanted

  • Good book on probability theory

  • Brain atlases

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