CSci 8363 Fall 2025 -- Ordered List of Papers

• full list of papers: https://www-users.cse.umn.edu/~boley/8363-25f/PaperList.htm
• class canvas site
• index.html (supplementary material)

Graphs and Random Walks

• 09/15 Monte Mahlum________________________
  Learning from Labeled and Unlabeled Data on a Directed Graph
  by Dengyong Zhou & Jiayuan Huang & Bernhard Schölkopf
  in ICML '05:
  https://www.semanticscholar.org/paper/Learning-from-labeled-and-unlabeled-data-on-a-graph-Zhou-Huang/df95ae968cb0b722143f6000fa0dc7ce21cc35e2
  https://pure.mpg.de/rest/items/item_1791381_2/component/file_3175263/content

• 09/17 Adam Imdieke_______________________
  Efficient Estimation of Word Representations in Vector Space
  by Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean
  https://arxiv.org/abs/1301.3781

• 09/17 Adam Imdieke_______________________
  Attention Is All You Need
  by Ashish Vaswani, Llion Jones, Noam Shazeer, Niki Parmar, Aidan N. Gomez, Jakob Uszkoreit, \L ukasz Kaiser, Illia Polosukhin
  https://arxiv.org/abs/1706.03762

Machine Learning

• 09/24 (postponed from 09/22): Archisman Bandyopadhyay ________
  Attention is a smoothed cubic spline
  by Zehua Lai, Lek-Heng Lim, Yucong Liu
  https://arxiv.org/abs/2408.09624

• 09/29 (postponed from 09/24): Brian Chung ________
  Dataset Distillation
  by Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, Alexei A. Efros
  https://arxiv.org/abs/1811.10959

• 10/01 (postponed from 09/29) Aadit Munjal _______________________
  ImageNet Classification with Deep Convolutional Neural Networks
  by Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton
  in NIPS 2012.
  https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks

• 10/01 (postponed from 09/29) Aadit Munjal _______________________
  Convolutional Networks and Applications in Vision
  by Yann LeCun & Koray Kavukvuoglu & Clement Farabet
  in Proc. International Symposium on Circuits and Systems (ISCAS'10) (IEEE), 2010
  https://yann.lecun.com/exdb/publis/pdf/lecun-iscas-10.pdf
  https://ieeexplore.ieee.org/document/5537907 (might require UofM login)

• 10/08 Monte Mahlum________________________
  The Singular Value Decompositions of Transformer Weight Matrices are Highly Interpretable
  by beren, Sid Black (2022)
  https://www.lesswrong.com/posts/mkbGjzxD8d8XqKHzA/the-singular-value-decompositions-of-transformer-weight

• 10/13 Adam Imdieke_______________________
  Propagative Distance Optimization for Constrained Inverse Kinematics
  by Yu Chen, Yilin Cai, Jinyun Xu, Zhongqiang Ren, Guanya Shi, Howie Choset
  https://arxiv.org/abs/2406.11572

• 10/15 Archisman Bandyopadhyay ___________
  Hodge Laplacian of Graphs
  by Lek-Heng Lim
  https://arxiv.org/abs/1507.05379

• 10/20 Brian Chung _______________________
  Deep Neural Networks as Gaussian Processes
  by Jaehoon Lee, Yasaman Bahri, Roman Novak, Samuel S. Schoenholz, Jeffrey Pennington, Jascha Sohl-Dickstein
  https://arxiv.org/abs/1711.00165

• 10/22 Aadit Munjal ______________________
  A ConvNet for the 2020s
  by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie
  https://arxiv.org/abs/2201.03545

• 10/27 Monte Mahlum________________________
  Sparse Autoencoders Find Highly Interpretable Features in Language Models
  by Hoagy Cunningham, Aidan Ewart, Logan Riggs, Robert Huben, Lee Sharkey
  https://arxiv.org/abs/2309.08600

• 10/29 Adam Imdieke_______________________
  Denoising Diffusion Probabilistic Models
  by Jonathan Ho, Ajay Jain, Pieter Abbeel
  https://arxiv.org/abs/2006.11239

• 11/03 Archisman Bandyopadhyay _____
  Generalization in Deep Learning
  by Kenji Kawaguchi, Leslie Pack Kaelbling, Yoshua Bengio
  https://arxiv.org/abs/1710.05468

• 11/05 Brian Chung _______________________
  Denoising Diffusion Implicit Models
  by Jiaming Song, Chenlin Meng, Stefano Ermon
  https://arxiv.org/abs/2010.02502

• 11/10 Aadit Munjal ______________________
  LOra: Low-Rank Adaptation Of Large Language Models
  by Edward Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen
  https://arxiv.org/abs/2106.09685

• 11/12 no class___________________________

• 11/17 Monte Mahlum_______________________
  graph neural networks with transformers
  Do Transformers Really Perform Bad for Graph Representation?
  by Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
  https://arxiv.org/abs/2106.05234
  ALSO: Hierarchical graph transformer with contrastive learning for protein function prediction
  by Zhonghui Gu, Xiao Luo, Jiaxiao Chen, Minghua Deng, Luhua Lai
  Bioinformatics, Volume 39, Issue 7, July 2023, btad410.
  https://academic.oup.com/bioinformatics/article/39/7/btad410/7208864

• 11/19 Adam Imdieke_______________________
  Mamba: Linear-Time Sequence Modeling with Selective State Spaces Albert
  by Albert Gu, Tri Dao
  https://arxiv.org/abs/2312.00752

• 11/24 Archisman Bandyopadhyay____________
  Discovering faster matrix multiplication algorithms with reinforcement learning
  by Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis & Pushmeet Kohli
  in Nature volume 610, pages 47–53 (2022)
  https://www.nature.com/articles/s41586-022-05172-4