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Paper Review

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.

List of Papers

  • Junyoung Chung, Sungjin Ahn, Yoshua Bengio, Hierarchical Multiscale Recurrent Neural Networks, ICLR 2017
  • Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi, AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks, ICLR 2019
  • Peters & Schaal, Reinforcement learning of motor skills with policy gradients, Neural Networks, 2008
  • Schulman et al, Trust Region Policy Optimization, ICML, 2015
  • Ho and Ermon, Generative Adversarial Imitation Learning, NIPS 2016
  • Arjovsky, M., & Bottou, L. Towards principled methods for training generative adversarial networks. ICLR 2017
  • Y. Song & S. Ermon, Generative Modeling by Estimating Gradients of the Data Distribution, NeurIPS 2019
  • Jonathan Ho et al, Denoising Diffusion Probabilistic Models, NeurIPS 2020
  • J. Austin, et al, Structured denoising diffusion models in discrete state-spaces, NeurIPS 2021
  • Kingma & Dhariwal, P, Glow: Generative flow with invertible 1x1 convolutions, NeurIPS 2018
  • G. Papamakarios et al, Masked Autoregressive Flow for Density Estimation, NeurIPS 2017
  • Aditya Ramesh et al. “Hierarchical Text-Conditional Image Generation with CLIP Latents." arxiv Preprint arxiv:2204.06125 (2022)
  • 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
  • B. Scellier and Y. Bengio, “Equilibrium Propagation: Bridging the Gap between Energy-Based Models and Backpropagation,” Frontiers in Computational Neuroscience, vol. 11, 2017
  • Petar Veličković, Rex Ying, Matilde Padovano, Raia Hadsell, Charles Blundell, Neural Execution of Graph Algorithms, ICLR 2020
  • F. Errica, D. Castellana, D. Bacciu, A. Micheli, The Infinite CGMM, ICML 2022
  • B. Chamberlain et al, Grand: Graph neural diffusion. ICML 2021
  • A. Gravina, D. Bacciu, C. Gallicchio, Anti-symmetric dgn: a stable architecture for deep graph networks, ICLR 2023
  • Phillip Lippe, Sara Magliacane, Sindy Löwe, Yuki M. Asano, Taco Cohen, Efstratios Gavves, CITRIS: Causal Identifiability from Temporal Intervened Sequences, ICML 2022
  • R Massidda, F Landolfi, M Cinquini, D Bacciu, Constraint-Free Structure Learning with Smooth Acyclic Orientations, ICLR 2024