| 2025 | ICLR | On the Benefits of Memory for Modeling Time-Dependent PDEs. | Ricardo Buitrago Ruiz, Tanya Marwah, Albert Gu, Andrej Risteski |
| 2025 | ICML | Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism. | Aviv Bick, Eric P. Xing, Albert Gu |
| 2025 | ICML | Understanding and Improving Length Generalization in Recurrent Models. | Ricardo Buitrago Ruiz, Albert Gu |
| 2025 | NAACL | Towards Codec-LM Co-design for Neural Codec Language Models. | Shih-Lun Wu, Aakash Lahoti, Arjun Desai, Karan Goel, Chris Donahue, Albert Gu |
| 2024 | ICASSP | Augmenting Conformers With Structured State-Space Sequence Models For Online Speech Recognition. | Haozhe Shan, Albert Gu, Zhong Meng, Weiran Wang, Krzysztof Choromanski, Tara N. Sainath |
| 2024 | ICML | Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality. | Tri Dao, Albert Gu |
| 2024 | ICML | Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling. | Yair Schiff, Chia-Hsiang Kao, Aaron Gokaslan, Tri Dao, Albert Gu, Volodymyr Kuleshov |
| 2023 | EMNLP | Pretraining Without Attention. | Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M. Rush |
| 2023 | ICLR | How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections. | Albert Gu, Isys Johnson, Aman Timalsina, Atri Rudra, Christopher R |
| 2023 | ICLR | Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN. | David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke |
| 2023 | ICML | Resurrecting Recurrent Neural Networks for Long Sequences. | Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, aglar Glehre, Razvan Pascanu, Soham De |
| 2022 | ICLR | Efficiently Modeling Long Sequences with Structured State Spaces. | Albert Gu, Karan Goel, Christopher R |
| 2022 | ICML | It's Raw! Audio Generation with State-Space Models. | Karan Goel, Albert Gu, Chris Donahue, Christopher R |
| 2021 | ICLR | Model Patching: Closing the Subgroup Performance Gap with Data Augmentation. | Karan Goel, Albert Gu, Sharon Li, Christopher R |
| 2021 | ICML | HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections. | Ines Chami, Albert Gu, Dat Nguyen, Christopher R |
| 2021 | ICML | Catformer: Designing Stable Transformers via Sensitivity Analysis. | Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher R, Chelsea Finn, Percy Liang |
| 2020 | ICALP | Sparse Recovery for Orthogonal Polynomial Transforms. | Anna C. Gilbert, Albert Gu, Christopher R, Atri Rudra, Mary Wootters |
| 2020 | ICLR | Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. | Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher R |
| 2020 | ICML | Improving the Gating Mechanism of Recurrent Neural Networks. | Albert Gu, aglar Glehre, Thomas Paine, Matt Hoffman, Razvan Pascanu |
| 2019 | ICLR | Learning Mixed-Curvature Representations in Product Spaces. | Albert Gu, Frederic Sala, Beliz Gunel, Christopher R |
| 2019 | ICML | Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. | Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher R |
| 2019 | ICML | A Kernel Theory of Modern Data Augmentation. | Tri Dao, Albert Gu, Alexander Ratner, Virginia Smith, Chris De Sa, Christopher R |
| 2018 | ICLR | Learning Invariance with Compact Transforms. | Anna T. Thomas, Albert Gu, Tri Dao, Atri Rudra, Christopher R |
| 2018 | ICML | Representation Tradeoffs for Hyperbolic Embeddings. | Frederic Sala, Christopher De Sa, Albert Gu, Christopher R |
| 2018 | SODA | A Two-pronged Progress in Structured Dense Matrix Vector Multiplication. | Christopher De Sa, Albert Gu, Rohan Puttagunta, Christopher R, Atri Rudra |
| 2013 | STOC | The power of deferral: maintaining a constant-competitive steiner tree online. | Albert Gu, Anupam Gupta, Amit Kumar |