====== Applied Brain Science - Computational Neuroscience (CNS) ====== ===== Lectures and Materials for Academic Year 2015/16 ===== ^ ^ Date ^ Room ^ Topic ^ References & Additional Material ^ | 1 | 29/2/16 (11.30-13.30) | SI 3 | Introduction to the course | {{:bionics-engineering:computational-neuroscience:cns-lez1-1.0.pdf|Lecture 1}} | | 2 | 02/3/16 (14.30-17.30) | C44 | Neural Modeling | {{:bionics-engineering:computational-neuroscience:bionics_neural_modeling.pdf|Lecture 2}} | | 3 | 07/3/16 (11.30-13.30) | SI 3 | Lab1 | Implementing Spiking Neurons using Izhikevich's Model | | 4 | 09/3/16 (15.30-18.30) | SI 3 | Neuron-Astrocyte models | {{:bionics-engineering:computational-neuroscience:neuro-astrocyte_modeling.pdf|Lecture 3}} | | 5 | 14/3/16 (11.30-13.30) | SI 3 | Lab2 | Implementing a Spiking Neural Network | | 6 | 16/3/16 (15.30-18.30) | SI 3 | In-vitro Models | Lecture 4: Statistics for In-vistro neuro-astrocyte culture | | 7 | 21/3/16 (11.30-13.30) | SI 3 | Lab3 | Implementing a Spiking Neuron-Astrocyte Network | | 8 | 04/04/16 (11.30-13.30) | SI 3 | Computation of Touch and Vision sensory input | {{:bionics-engineering:computational-neuroscience:lecture_prof.wanke_touch_vision_040416.pdf|Lecture 5}} | | 9 | 06/04/16 (15.30-18.30) | SI 3 | Introduction to Unsupervised and Representation Learning | {{bionics-engineering:computational-neuroscience:1-unsuplearn-hand.pdf|Lecture 6}}\\ //References//:\\ [DAYAN] Sect. 8.1-8.3\\ [PANINSKI] Sect 19.1, 19.2.1, 19.3.1, 19.3.2 | | 10 | 11/04/16 (11.30-13.30) | SI 3 | Associative Memories I - Hopfield Networks | {{bionics-engineering:computational-neuroscience:2-hopfield-hand.pdf|Lecture 7}}\\ //References//:\\ [DAYAN] Sect. 7.4 (Associative Memory part)\\ [PANINSKI] Sect. 17.1, 17.2 | | 11 | 13/04/16 (15.30-18.30) | SI 3 | Lab 4 | Hebbian learning and Hopfield networks ([[lab4|Assignment 4]]) | | 12 | 18/04/16 (11.30-13.30) | SI 3 | Associative Memories II - Stochastic networks and Boltzmann machines | {{bionics-engineering:computational-neuroscience:3-boltz-hand.pdf|Lecture 8}}\\ //References//:\\ [DAYAN] Sect. 7.6\\ \\ //Further readings//:\\ [[bionics-engineering:computational-neuroscience:start#further_readings|[1]]] A clean and clear introduction to RBM | | 13 | 20/04/16 (15.30-18.30) | SI 3 | Lab 5 | Boltzmann machines ([[lab5|Assignment 5]])| | | 25/04/16 (11.30-13.30) | SI 3 | No class due to [[https://en.wikipedia.org/wiki/Liberation_Day_%28Italy%29|Italian national holiday]] | | | | 27/04/16 (15.30-18.30) | SI 3 | No class | | | 14 | 02/05/16 (11.30-13.30) | SI 3 | Representation learning and deep learning models | {{bionics-engineering:computational-neuroscience:5-deep-hand.pdf|Lecture 9}}\\ //References//:\\ [DAYAN] Sect. 10.1\\ \\ //Further Readings//:\\ [[bionics-engineering:computational-neuroscience:start#further_readings|[2]]] A classic divulgative paper from the initiator of Deep Learning \\ [[bionics-engineering:computational-neuroscience:start#further_readings|[3]]] Recent review paper \\ [[bionics-engineering:computational-neuroscience:start#further_readings|[4]]] A freely available book on deep learning from Microsoft RC | | 15 | 04/05/16 (15.30-18.30) | SI 3 | Lecture: Adaptive Resonance Theory (ART) \\ Lab 6 | {{bionics-engineering:computational-neuroscience:4-art-hand.pdf|Lecture 10}}\\ Deep RBM ([[lab6|Optional Assignment 6]])\\ \\ //Futher Readings//:\\ A gentle introduction to ART networks (with coding examples) can be found [[http://cannes.itam.mx/Alfredo/English/Publications/Nslbook/MitPress/157_170.CH08.pdf|here]]| | 16 | 09/05/16 (11.30-13.30) | SI 3 | Introduction to RNN: tasks and basic models | [[http://www.di.unipi.it/~micheli/DID/CNS/CNS-2016/part3/| Lecture and info multifiles]] | | 17 | 11/05/16 (15.30-18.30) | SI 3 | Introduction to RNN: properties and taxonomy; intro to learning by BPTT | [[http://www.di.unipi.it/~micheli/DID/CNS/CNS-2016/part3/| Lecture and info multifiles (also RNN learning)]] | | 18 | 16/05/16 (11.30-13.30) | SI 3 | Introduction to RNN: learning by RTRL| [[http://www.di.unipi.it/~micheli/DID/CNS/CNS-2016/part3/| Lecture and info multifiles (RNN learning)]] plus blackboard notes| | 19 | 18/05/16 (15.30-18.30) | SI 3 | Introduction to RNN: LAB 1 - learning with IDNN and RNN| [[http://www.di.unipi.it/~micheli/DID/CNS/CNS-2016/part3/| Info and assignment multifiles (see "RNN - Lab1" section)]] | | 20 | 23/05/16 (11.30-13.30) | SI 3 | Introduction to RNN: Reservoir Computing | [[http://www.di.unipi.it/~micheli/DID/CNS/CNS-2016/part3/| Lecture and info multifiles (ESN)]] | | 21 | 25/05/16 (15.30-18.30) | SI 3 | Introduction to RNN: LAB 2 - learning with ESN | [[http://www.di.unipi.it/~micheli/DID/CNS/CNS-2016/part3/| Info and assignment multifiles (see "RNN - Lab2" section). NEW: See also the new "Upgrade" section for further clarification ]] |