Plan for Fall 2019

Timeline View (Version 1.0)



Paper Reading List

I. Theory of Deep Learning

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Reinforcement Learning

II. Application of Deep Learning

Biomedical Image Analysis

Protein Function Prediction

  • A Reinforcement Learning Based Approach to Multiple Sequence Alignment. Ioan-Gabriel Mircea, Iuliana Bocicor, Gabriela Czibula. In: Balas V., Jain L., Balas M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 634. [https://link.springer.com/chapter/10.1007/978-3-319-62524-9_6]
  • Using deep reinforcement learning approach for solving the multiple sequence alignment problem. Jafari, R., Javidi, M. & Kuchaki Rafsanjani, M. SN Appl. Sci. (2019) 1: 592. [https://doi.org/10.1007/s42452-019-0611-4]

Protein Secondary Structure Prediction

  • Papers to read: Link.

Neuro-inspired DL Systems and Algorithms

III. Implementation of Deep Learning

  • Chollet, F. (2015) Keras, GitHub. https://github.com/fchollet/keras.

Top Conferences for Machine Learning & Artificial Intelligence

More papers to read (Link)