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Intelligent Systems for Pattern Recognition - 9 CFU

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Midterm 4 (2025)

Completion requirements
Due: Friday, 27 June 2025, 6:00 PM

Assignment Rules and Execution

The fourth midterm covers the program until lecture 36. Differently from the previous ones, this midterm is based on reading and summarizing the main findings of a single paper chosen from the list provided below. 

Students are expected to deliver a short presentation (no more than 8 slides) covering the following content:

  1. Introduction to the problem
  2. Model description
  3. Key catch of the model, represented by a commented equation
  4. Key (empirical) result
  5. Comment on novelties, strong points and weaknesses
I will pay particular attention to the technical depth and understanding of the paper which you will convey through point 3 above.  As usual the presentation (in PDF please) should be upload here by the (strict) deadline.
 

List of papers

  1. Junyoung Chung, Sungjin Ahn, Yoshua Bengio, Hierarchical Multiscale Recurrent Neural Networks, ICLR 2017
  2. Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi, AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks, ICLR 2019
  3. Peters & Schaal, Reinforcement learning of motor skills with policy gradients, Neural Networks, 2008
  4. Schulman et al, Trust Region Policy Optimization, ICML, 2015
  5. Ho and Ermon, Generative Adversarial Imitation Learning, NIPS 2016
  6. Arjovsky, M., & Bottou, L. Towards principled methods for training generative adversarial networks. ICLR 2017
  7. Y. Song & S. Ermon, Generative Modeling by Estimating Gradients of the Data Distribution, NeurIPS 2019
  8. Jonathan Ho et al, Denoising Diffusion Probabilistic Models, NeurIPS 2020
  9. J. Austin, et al,  Structured denoising diffusion models in discrete state-spaces, NeurIPS 2021
  10. Kingma & Dhariwal, P, Glow: Generative flow with invertible 1x1 convolutions, NeurIPS 2018
  11. G. Papamakarios et al, Masked Autoregressive Flow for Density Estimation, NeurIPS 2017
  12. Aditya Ramesh et al. “Hierarchical Text-Conditional Image Generation with CLIP Latents." arxiv Preprint arxiv:2204.06125 (2022)
  13. Andrea Ceni, Andrea Cossu, Maximilian W Stölzle, Jingyue Liu, Cosimo Della Santina, Davide Bacciu, Claudio Gallicchio, Random Oscillators Network for Time Series Processing, AISTATS 2024
  14. B. Scellier and Y. Bengio, “Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation,” Frontiers in Computational Neuroscience, vol. 11, 2017
  15. Petar Veličković, Rex Ying, Matilde Padovano, Raia Hadsell, Charles Blundell, Neural Execution of Graph Algorithms, ICLR 2020
  16. F. Errica, D. Castellana, D. Bacciu, A. Micheli, The Infinite CGMM, ICML 2022
  17. B. Chamberlain et al, Grand: Graph neural diffusion. ICML 2021
  18. A. Gravina, M. Eliasof, C. Gallicchio, D. Bacciu, & C.-B. Schönlieb On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems. AAAI 2025, Full paper here: https://arxiv.org/pdf/2405.01009
  19. Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves, CITRIS: Causal Identifiability from Temporal Intervened Sequences, ICML 2022
  20. R Massidda, F Landolfi, M Cinquini, D Bacciu, Constraint-Free Structure Learning with Smooth Acyclic Orientations, ICLR 2024
  21. Dao Tri, Albert Gu, Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality, ICLR 2024, https://arxiv.org/pdf/2405.21060

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          • Intelligent Systems for Pattern Recognition - 9 CFU

          • Course Information

          • Introduction (2h)

          • Fundamentals of Pattern Recognition (6h)

          • Probabilistic (Generative) Learning (30h)

          • Deep Learning (18h)

          • Generative Deep Learning (10h)

          • Advanced Topics and Applications (8h)

          • Course Grading and Exams

          • Midterms and Projects

            • AssignmentMidterm 1 (2025)

            • AssignmentMidterm 2 (2025)

            • AssignmentMidterm 3 (2025)

            • AssignmentMidterm 4 (2025)

            • AssignmentFinal Projects (2025)

            • AssignmentFinal Project Delivery - Session 3 (Summer 2025)

            • AssignmentFinal Project Delivery - Session 4 (Summer 2025)

            • AssignmentFinal Project Delivery - Session 5 (Summer 2025)

            • AssignmentFinal Project Delivery - Session 10 (Spring 2025, ...

          • Bibliography

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