Tyler Scott
Citata da
Citata da
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning
TR Scott, K Ridgeway, MC Mozer
Advances in Neural Information Processing Systems, 76-85, 2018
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning
TR Scott, AC Gallagher, MC Mozer
IEEE/CVF International Conference on Computer Vision, 2021
Stochastic Prototype Embeddings
TR Scott, K Ridgeway, MC Mozer
ICML Workshop on Uncertainty and Robustness in Deep Learning, 2019
Learning in Temporally Structured Environments
M Jones, TR Scott, M Ren, GF Elsayed, K Hermann, D Mayo, MC Mozer
The Eleventh International Conference on Learning Representations, 2022
Multitask learning via interleaving: A neural network investigation
D Mayo, TR Scott, M Ren, G Elsayed, K Hermann, M Jones, M Mozer
Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45), 2023
Online Unsupervised Learning of Visual Representations and Categories
M Ren, TR Scott, ML Iuzzolino, MC Mozer, R Zemel
arXiv preprint arXiv:2109.05675, 2021
An Empirical Study on Clustering Pretrained Embeddings: Is Deep Strictly Better?
TR Scott, T Liu, MC Mozer, AC Gallagher
arXiv preprint arXiv:2211.05183, 2022
Neural Network Online Training With Sensitivity to Multiscale Temporal Structure
M Jones, D Mayo, T Scott, M Ren, G ElSayed, K Hermann, MC Mozer
NeurIPS Workshop on Memory in Artificial and Real Intelligence, 2022
Unifying Few- and Zero-Shot Egocentric Action Recognition
TR Scott, M Shvartsman, K Ridgeway
CVPR Workshop on Egocentric Perception, Interaction, and Computing, 2020
Deep Visual Representation Learning for Classification and Retrieval: Uncertainty, Geometry, and Applications
TR Scott
University of Colorado at Boulder, 2023
Using Semantics of Textbook Highlights to Predict Student Comprehension and Knowledge Retention
DYJ Kim, TR Scott, D Mallick, M Mozer
AIED Workshop on Intelligent Textbooks, 2021
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Articoli 1–11