7 |
6 |
7 |
,
10 | 
11 |
12 |
13 | 2. **Simplicial 2-Complex Convolutional Neural Nets**. Eric Bunch, Qian You, Glenn Fung, Vikas Singh. *NeurIPS 2020 Workshop TDA and Beyond*. [Paper](https://openreview.net/pdf?id=TLbnsKrt6J-), [Code](https://github.com/AmFamMLTeam/simplicial-2-complex-cnns)
14 |
15 | 3. **Cell complex neural networks**. Mustafa Hajij, Kyle Istvan, and Ghada Zamzmi. *NeurIPS Workshop on Topological Data Analysis and Beyond, 2020*. [Paper](https://openreview.net/pdf?id=6Tq18ySFpGU),
16 |
17 | 4. **Principled simplicial neural networks for trajectory prediction**. Roddenberry, T. Mitchell, Nicholas Glaze, and Santiago Segarra. *ICML 2021*. [Paper](http://proceedings.mlr.press/v139/roddenberry21a/roddenberry21a.pdf), [Code](https://github.com/nglaze00/SCoNe_GCN) 
18 |
19 | 5. **Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks**. Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael Bronstein. *ICML 2021*. [Paper](http://proceedings.mlr.press/v139/bodnar21a/bodnar21a.pdf), [Code](https://github.com/twitter-research/cwn) ,
20 |
21 |
22 |
23 | 6. **Weisfeiler and Lehman Go Cellular: CW Networks**. Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael Bronstein. *NeurIPS 2021*. [Paper](https://proceedings.neurips.cc/paper/2021/file/157792e4abb490f99dbd738483e0d2d4-Paper.pdf), [Code](https://github.com/twitter-research/cwn) ,
24 |
25 |
26 |
27 | 7. **Simplicial Attention Neural Networks**. Lorenzo Giusti, Claudio Battiloro, Paolo Di Lorenzo, Stefania Sardellitti, Sergio Barbarossa. *arXiv 2022*. [Paper](https://arxiv.org/abs/2203.07485), [Code](https://github.com/lrnzgiusti/simplicial-attention-networks)
28 |
29 | 8. **Simplicial Attention Networks**. Christopher Wei Jin Goh, Cristian Bodnar, Pietro Liò. *ICLR 2022 Workshop on Geometrical and Topological Representation Learning*. [Paper](https://arxiv.org/abs/2204.09455), [Code](https://github.com/ggoh29/Simplicial-neural-network-benchmark)
30 |
31 | 9. **Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs**. Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Liò, Michael M. Bronstein. *NeurIPS 2022*. [Paper](https://arxiv.org/abs/2202.04579), [Code](https://github.com/twitter-research/neural-sheaf-diffusion) ,
32 |
33 |
34 |
35 | 10. **Simplicial Convolutional Neural Networks**. Maosheng Yang, Elvin Isufi, Geert Leus. *ICASSP 2022*. [Paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9746017&casa_token=Qg3EgJQy7dkAAAAA:zir5JmgmjZBArJNQuatXU1z4L-z5FqruCyONv7aUuNXPxokdayx6d3C9Nj06ng5CXTl3mgc), [Code](https://github.com/cookbook-ms/simplicial_convolutional_neural_networks)
36 |
37 | 11. **Sheaf Neural Networks with Connection Laplacians**. Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael Bronstein, Petar Veličković, Pietro Liò. *ICML 2022 Workshop on Topology, Algebra, and Geometry in Machine Learning*. [Paper](https://arxiv.org/abs/2206.08702)
38 |
39 | 12. **Sheaf Attention Networks**. Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Pietro Liò. *NeurIPS 2022 NeurReps Workshop*. [Paper](https://openreview.net/pdf?id=LIDvgVjpkZr)
40 |
41 | 13. **Cell Attention Networks**. Lorenzo Giusti, Claudio Battiloro, Lucia Testa, Paolo Di Lorenzo, Stefania Sardellitti, Sergio Barbarossa. *IEEE IJCNN 2023*. [Paper](https://arxiv.org/abs/2209.08179), [Code](https://github.com/lrnzgiusti/can)
42 |
43 | 14. **Surfing on the Neural Sheaf**. Julian Suk, Lorenzo Giusti, Tamir Hemo, Miguel Lopez, Konstantinos Barmpas, Cristian Bodnar. *NeurIPS 2022 NeurReps Workshop*. [Paper](https://openreview.net/pdf?id=xOXFkyRzTlu)
44 |
45 | 15. **Architectures of Topological Deep Learning: A Survey on Topological Neural Networks**. Mathilde Papillon, Sophia Sanborn, Mustafa Hajij, Nina Miolane. [Paper](https://arxiv.org/abs/2304.10031)
46 |
47 | 16. **Tangent Bundle Convolutional Learning: from Manifolds to Cellular Sheaves and Back**. Claudio Battiloro, Zhiyang Wang, Hans Riess, Paolo Di Lorenzo, Alejandro Ribeiro. [Paper](https://arxiv.org/abs/2303.11323), [Code](https://github.com/clabat9/Tangent-Bundle-Neural-Networks)
48 |
49 | 17. **Topological Graph Neural Networks**. Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, and Karsten Borgwardt. *ICLR 2022*. [Paper](https://openreview.net/pdf?id=oxxUMeFwEHd), [Code](https://github.com/BorgwardtLab/TOGL) ,
50 |
51 |
52 |
53 | 18. **Topological Autoencoders**. Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt. *ICML 2020*. [Paper](https://proceedings.mlr.press/v119/moor20a.html), [Code](https://github.com/BorgwardtLab/topological-autoencoders)
54 |
55 | 19. **E(n) Equivariant Message Passing Simplicial Networks**. Floor Eijkelboom, Rob Hesselink, Erik Bekkers. *ICML 2023*. [Paper](https://arxiv.org/abs/2305.07100)
56 |
57 | 20. **CIN++: Enhancing Topological Message Passing**. Lorenzo Giusti, Teodora Reu, Francesco Ceccarelli, Cristian Bodnar, Pietro Liò. [Paper](https://arxiv.org/abs/2306.03561), [Code](https://github.com/twitter-research/cwn)
58 |
59 | 21. **Simplicial Hopfield networks**. Thomas F Burns, Tomoki Fukai. *ICLR 2023*. [Paper](https://arxiv.org/abs/2305.05179), [Code](https://github.com/tfburns/simplicial-hopfield-networks),
60 |
61 |
62 |
63 | 22. **Topological Deep Learning: Graphs, Complexes, Sheaves**. Cristian Bodnar. [Thesis](https://www.repository.cam.ac.uk/handle/1810/350982)
64 |
65 | 23. **Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes**. Quang Truong and Peter Chin. *AAAI 2024*. [Paper](https://arxiv.org/abs/2308.06838), [Code](https://github.com/quang-truong/Path-Complex-Networks)
66 |
67 | 24. **Generalized simplicial attention neural networks**. Claudio Battiloro, Lucia Testa, Lorenzo Giusti, Stefania Sardellitti, Paolo Di Lorenzo, Sergio Barbarossa. [Paper](https://arxiv.org/abs/2309.02138)
68 |
69 | 25. **TopoX: A Suite of Python Packages for Machine Learning on Topological Domains**. Mustafa Hajij, Mathilde Papillon, Florian Frantzen et al. [Paper](https://arxiv.org/abs/2402.02441), [Code](https://github.com/pyt-team/TopoNetX)
70 |
71 | 26. **Topological Neural Networks: Mitigating the Bottlenecks of Graph Neural Networks via Higher-Order Interactions**. Lorenzo Giusti. [Thesis](https://arxiv.org/abs/2402.06908)
72 |
73 | 27. **From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module**. Claudio Battiloro, Indro Spinelli et al. [Paper](https://openreview.net/forum?id=0JsRZEGZ7L), [Code](https://github.com/spindro/differentiable_cell-complex_module), [Blogpost](https://clabat9.medium.com/latent-topology-inference-0a3c04bf0fa5)
74 |
75 | 27. **E(n) Equivariant Topological Neral Networks**. Claudio Battiloro, Ege Karaismailoğlu, Mauricio Tec, George Dasoulas et al. [Paper](https://arxiv.org/abs/2405.15429), [Code](https://github.com/NSAPH-Projects/topological-equivariant-networks), [Blogpost](https://clabat9.medium.com/e-n-equivariant-topological-neural-networks-3117f582d6bf)
76 |
77 | 28. **Signal Processing and Learning over Topological Spaces**. Claudio Battiloro. [Thesis](https://theses.eurasip.org/theses/974/signal-processing-and-learning-over-topological/)
78 |
79 | 29. **Gaussian Processes on Cellular Complexes**. Mathieu Alain, So Takao, Brooks Paige, Marc Peter Deisenroth. *ICML 2024*. [Paper](https://proceedings.mlr.press/v235/alain24a.html)
80 |
81 | 30. **TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks**. Mathilde Papillon, Guillermo Bernárdez, Claudio Battiloro, and Nina Miolane. [Paper](https://arxiv.org/abs/2410.06530), [Code](https://github.com/geometric-intelligence/TopoBenchmark?tab=readme-ov-file#bulb-topotune)
82 |
83 | 31. **Molecular topological deep learning for polymer property prediction**. Cong Shen, Yipeng Zhang, Fei Han, Kelin Xia. [Paper](https://arxiv.org/abs/2410.04765)
84 |
85 | 32. **Bayesian Sheaf Neural Networks**. Patrick Gillespie, Vasileios Maroulas, Ioannis Schizas. [Paper](https://arxiv.org/abs/2410.09590)
86 |
87 | 33. **Higher-Order Topological Directionality and Directed Simplicial Neural Networks**. Manuel Lecha, Andrea Cavallo, Francesca Dominici, Elvin Isufi, Claudio Battiloro. [Paper](https://arxiv.org/abs/2409.08389), [Code](https://github.com/andrea-cavallo-98/DirSNN)
88 |
89 | 34. **TopoBenchmarkX: A Framework for Benchmarking Topological Deep Learning**. Lev Telyatnikov, Guillermo Bernardez, Marco Montagna, Pavlo Vasylenko, Ghada Zamzmi, Mustafa Hajij, Michael T Schaub, Nina Miolane, Simone Scardapane, Theodore Papamarkou. [Paper](https://arxiv.org/abs/2406.06642), [Code](https://github.com/geometric-intelligence/TopoBenchmark)
90 |
91 | 35. **Topological Network Traffic Compression**. Guillermo Bernárdez, Lev Telyatnikov, Eduard Alarcón, Albert Cabellos-Aparicio, Pere Barlet-Ros, Pietro Liò. *Proceedings of the 2nd on Graph Neural Networking Workshop 2023.* [Paper](https://dl.acm.org/doi/abs/10.1145/3630049.3630172)
92 |
93 | 36. **Topological Deep Learning : Going Beyond Graph Data**. Mustafa Hajij, Theodore Papamarkou, Ghada Zamzmi, Karthikeyan Natesan Ramamurthy, Tolga Birdal, Michael T. Schaub [Book](https://tdlbook.org/)
94 |
95 | 37. **HOG-Diff: Higher-Order Guided Diffusion for Graph Generation**. Huang, Yiming, and Tolga Birdal. arXiv preprint arXiv:2502.04308 (2025). [Paper](https://arxiv.org/pdf/2502.04308), [Code](https://github.com/Yiminghh/HOG-Diff)
96 |
97 | ---
98 |
99 | ### Topological Signal Processing
100 | 1. **Topological signal processing over simplicial complexes**. Sergio Barbarossa, Stefania Sardellitti. *IEEE Transactions on Signal Processing 2020*. [Paper](https://arxiv.org/abs/1907.11577)
101 | 2. **Signal processing on higher-order networks: Livin’ on the edge... and beyond**. Michael T. Schaub, Yu Zhu, Jean-Baptiste Seby, T. Mitchell Roddenberry, Santiago Segarra. *Signal Processing, 2021 - Elsevier* [Paper](https://arxiv.org/abs/2101.05510)
102 | 3. **Hodge Laplacians on Graphs**. Lek-Heng Lim. *Society for Industrial and Applied Mathematics 2020*. [Paper](https://epubs.siam.org/doi/pdf/10.1137/18M1223101)
103 | 4. **Random Walks on Simplicial Complexes and the normalized Hodge 1-Laplacian**. Michael T. Schaub, Austin R. Benson, Paul Horn, Gabor Lippner, Ali Jadbabaie. *SIAM 2020*. [Paper](https://epubs.siam.org/doi/pdf/10.1137/18M1201019?casa_token=3_n5OReMfD8AAAAA:1al8NfUIgAK5Gu0SiiHvNjgTVvrcX6uc9EhF0IZcd9V58JefCh4GUnWItVYFGFvAnhNIOo7v)
104 | 5. **What are higher-order networks?** Christian Bick, Elizabeth Gross, Heather A. Harrington, Michael T. Schaub. *arXiv 2021*. [Paper](https://arxiv.org/abs/2104.11329)
105 | 6. **Topological Signal Processing over Cell Complexes**. Stefania Sardellitti, Sergio Barbarossa, Lucia Testa. *arXiv 2021*. [Paper](https://arxiv.org/abs/2112.06709)
106 | 7. **Topological Signal Representation and Processing over Cell Complexes**. Stefania Sardellitti, Sergio Barbarossa. *arXiv 2022*. [Paper](https://arxiv.org/abs/2201.08993)
107 | 8. **Robust Signal Processing Over Simplicial Complexes**. Stefania Sardellitti, Sergio Barbarossa. *ICASSP 2022*. [Paper](https://ieeexplore.ieee.org/abstract/document/9746761/)
108 | 9. **The physics of higher-order interactions in complex systems**. Battiston, Federico, Enrico Amico, Alain Barrat, Ginestra Bianconi, Guilherme Ferraz de Arruda, Benedetta Franceschiello, Iacopo Iacopini et al. *Nature Physics* [Paper](https://www.nature.com/articles/s41567-021-01371-4)
109 | 10. **Recovery of Signals on a Simplicial Complex from Subsampled Neighbourhood Aggregation**. Siddartha Reddy; Sundeep Prabhakar Chepuri. *IEEE Signal Processing Letters* [Paper](https://ieeexplore.ieee.org/abstract/document/10706807)
110 | ---
111 |
112 | ### Algebraic Topology
113 |
114 | 1. **Computational and applied topology, tutorial**. Paweł Dłotko. *2018*. [Paper](https://arxiv.org/abs/1807.08607)
115 | 2. **Algebraic topology**. Allen Hatcher. *Cambridge Univ. Press. 2000*. [Book](http://pi.math.cornell.edu/~hatcher/AT/AT.pdf)
116 | 3. **Cell Complexes through Time**. Reinhard Klette. *Vision Geometry 2000*. [Paper](https://www.maths.ed.ac.uk/~v1ranick/papers/klette.pdf)
117 | ---
118 |
119 | ### Differential Geometry
120 |
121 | 1. **Introduction to Differential Geometry**. Joel W. Robbin, Dietmar A. Salamon. [Book](https://people.math.ethz.ch/~salamon/PREPRINTS/diffgeo.pdf)
122 | 2. **Differential Geometry and Stochastic Dynamics with Deep Learning Numerics** Line Kühnel, Alexis Arnaudon, and Stefan Sommer. *arXiv 2017*. [Paper](https://arxiv.org/pdf/1712.08364.pdf)
123 | 3. **Differential Geometry meets Deep Learning (DiffGeo4DL)** Joey Bose · Emile Mathieu · Charline Le Lan · Ines Chami · Frederic Sala · Christopher De Sa · Maximilian Nickel · Christopher Ré · Will Hamilton. *NeurIPS 2020 Workshop*. [Link](https://nips.cc/Conferences/2020/ScheduleMultitrack?event=16116)
124 | ---
125 |
126 | ### Discrete Calculus
127 | 1. **Discrete Exterior Calculus**. Anil N. Hirani. *Caltech Library 2003*. [PhD Thesis](https://thesis.library.caltech.edu/1885/3/thesis_hirani.pdf)
128 |
129 | 2. **Discrete Calculus: Applied Analysis on Graphs for Computational Science**. Leo J. Grady, Jonathan R. Polimeni. *Springer 2010* . [Book](http://leogrady.net/wp-content/uploads/2017/01/grady2010discrete.pdf)
130 | 3. **Discrete Differential Forms for Computational Modeling**. Mathieu Desbrun, Eva Kanso & Yiying Tong. *SIGGRAPH 2006*. [Paper](https://dl.acm.org/doi/pdf/10.1145/1185657.1185665?casa_token=K71FDD1wHvAAAAAA:BtLvvN-ChokfibpRnGZAOSNvBW4Qy0ZkiasCFoL3PovzI4TKqBAZz8W8aGb9wgSb1WG8gQmyvsIH)
131 | ---
132 |
133 | ### Courses
134 |
135 | 1. **Computational Algebraic Topology**. Vidit Nanda. [Website](https://people.maths.ox.ac.uk/nanda/cat/), [Notes](https://people.maths.ox.ac.uk/nanda/cat/TDANotes.pdf), [Lectures](https://www.youtube.com/playlist?list=PLnLAqsCN_2ke8_EUd_KoJsLkPO0BKrrc6)
136 |
137 |
138 | 
139 |
144 | 
145 |
150 | 
151 |