266 citations · 559 across the 19 of their papers we have counts for
13 papers · 1 filter
Challenges for cognitive decoding using deep learning methods
Armin W. Thomas, Christopher Ré, Russell A. Poldrack
In cognitive decoding, researchers aim to characterize a brain region's representations by identifying the cognitive states (e.g., accepting/rejecting a gamble) that can be identif…
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections
Ines Chami, Albert Gu, Dat Nguyen +1
This paper studies Principal Component Analysis (PCA) for data lying in hyperbolic spaces. Given directions, PCA relies on: (1) a parameterization of subspaces spanned by these dir…
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps
Tri Dao, Nimit S. Sohoni, Albert Gu +5
Modern neural network architectures use structured linear transformations, such as low-rank matrices, sparse matrices, permutations, and the Fourier transform, to improve inference…
Understanding and Improving Information Transfer in Multi-Task Learning
Sen Wu, Hongyang R. Zhang, Christopher Ré
We investigate multi-task learning approaches that use a shared feature representation for all tasks. To better understand the transfer of task information, we study an architectur…
Low-Dimensional Hyperbolic Knowledge Graph Embeddings
Ines Chami, Adva Wolf, Da-Cheng Juan +3
Knowledge graph (KG) embeddings learn low-dimensional representations of entities and relations to predict missing facts. KGs often exhibit hierarchical and logical patterns which…
Ivy: Instrumental Variable Synthesis for Causal Inference
Zhaobin Kuang, Frederic Sala, Nimit Sohoni +5
A popular way to estimate the causal effect of a variable x on y from observational data is to use an instrumental variable (IV): a third variable z that affects y only through x.…