activity
20142026
most citedDeep Learning Models of the Retinal Response to Natural Scenes

167 citations · 533 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Reinforcement Learning on Cost-Constrained Quadrupedal Hardware

Javier C. Weddington, Bence P. Ölveczky, Stephen A. Baccus

Deploying learned control policies on low-cost robotic platforms introduces transport latencies and noisy motor feedback that systematically widens the sim-to-real gap. The chasm o…

cs.LG2026

Causal Interpretation of Neural Network Computations with Contribution Decomposition

Joshua Brendan Melander, Zaki Alaoui, Shenghua Liu +2

Understanding how neural networks transform inputs into outputs is crucial for interpreting and manipulating their behavior. Most existing approaches analyze internal representatio…

cs.LG2023★ 157 cited

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution

Eric Nguyen, Michael Poli, Marjan Faizi +10

Genomic (DNA) sequences encode an enormous amount of information for gene regulation and protein synthesis. Similar to natural language models, researchers have proposed foundation…

cs.LG2023★ 75 cited

Hyena Hierarchy: Towards Larger Convolutional Language Models

Michael Poli, Stefano Massaroli, Eric Nguyen +6

Recent advances in deep learning have relied heavily on the use of large Transformers due to their ability to learn at scale. However, the core building block of Transformers, the…

cs.CV2022★ 8 cited

S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces

Eric Nguyen, Karan Goel, Albert Gu +5

Visual data such as images and videos are typically modeled as discretizations of inherently continuous, multidimensional signals. Existing continuous-signal models attempt to expl…

q-bio.NC2019★ 43 cited

From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction

Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan +3

Recently, deep feedforward neural networks have achieved considerable success in modeling biological sensory processing, in terms of reproducing the input-output map of sensory neu…