Albert Gu
32 papers · 2018–2025 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+12 more ↓ Show less ↑
π Conference Polyglot (5) π Academic Marathon (7) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird
πΊοΈ
Taxonomy Completionist
(43)
π
Conference Polyglot
(5)
π
Academic Marathon
(7)
π§¬
Topic Evolution
π
Triple Crown
π
Keyword Champion
(5)
π€
Dynamic Duo
(18)
ποΈ
Keyword Collector
(92)
β‘
Prolific Year
(5)
π
Century Club
(32)
π₯
Unstoppable
(8)
π
Trend Setter
Conferences
ICML (12)
NIPS (11)
ICLR (7)
EMNLP (1)
NAACL (1)
Top co-authors
Research topics
Keywords
state space model
(6)
sequence modeling
(5)
recurrent neural network
(5)
sequence model
(3)
model architecture
(3)
state-space model
(3)
model compression
(3)
dimensionality reduction
(2)
representation learning
(2)
long-range dependency
(2)
hyperbolic embedding
(2)
parallel training
(2)
long sequence modeling
(2)
long-range dependencies
(2)
data augmentation
(1)
knowledge distillation
(1)
attention mechanism
(1)
video classification
(1)
structured matrix
(1)
principal component analysis
(1)
Papers
Understanding and Improving Length Generalization in Recurrent Models
ICML 2025
Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism
ICML 2025
On the Benefits of Memory for Modeling Time-Dependent PDEs
ICLR 2025
Towards Codec-LM Co-design for Neural Codec Language Models
NAACL 2025
Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers
NIPS 2024
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models
NIPS 2024
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
ICML 2024
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
ICML 2024
How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections
ICLR 2023
Structured State Space Models for In-Context Reinforcement Learning
NIPS 2023
Pretraining Without Attention
EMNLP 2023
Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN
ICLR 2023
Resurrecting Recurrent Neural Networks for Long Sequences
ICML 2023
Efficiently Modeling Long Sequences with Structured State Spaces
ICLR 2022
On the Parameterization and Initialization of Diagonal State Space Models
NIPS 2022
Diagonal State Spaces are as Effective as Structured State Spaces
NIPS 2022
S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces
NIPS 2022
Itβs Raw! Audio Generation with State-Space Models
ICML 2022
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections
ICML 2021
Catformer: Designing Stable Transformers via Sensitivity Analysis
ICML 2021
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers
NIPS 2021
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
ICLR 2021
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps
ICLR 2020
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering
NIPS 2020
Improving the Gating Mechanism of Recurrent Neural Networks
ICML 2020
HiPPO: Recurrent Memory with Optimal Polynomial Projections
NIPS 2020
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems
NIPS 2020
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations
ICML 2019
A Kernel Theory of Modern Data Augmentation
ICML 2019
Learning Mixed-Curvature Representations in Product Spaces
ICLR 2019
Representation Tradeoffs for Hyperbolic Embeddings
ICML 2018
Learning Compressed Transforms with Low Displacement Rank
NIPS 2018