Jason Yosinski
18 papers · 2014–2021 · 5 conferences · across top CS/AI conferences
Achievements
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š Academic Marathon (7) š Conference Polyglot (5) š Interdisciplinary Bridge š§ Keyword Pioneer š£ Hot Topic Early Bird
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Keyword Pioneer
š£
Hot Topic Early Bird
š
Conference Polyglot
(5)
š
Keyword Trendsetter Combo
(6)
š§¬
Topic Evolution
š
Triple Crown
š
Trend Setter
š
Conference Pioneer
šļø
Keyword Collector
(82)
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Unstoppable
(8)
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The Questioner
š
Century Club
(18)
Conferences
NIPS (9)
CVPR (3)
ICML (3)
ICLR (2)
EMNLP (1)
Top co-authors
Keywords
convolutional neural network
(4)
image generation
(3)
neural network
(3)
neural network pruning
(2)
image classification
(2)
activation maximization
(2)
representation learning
(2)
gradient-based optimization
(1)
transfer learning
(1)
continual learning
(1)
few-shot learning
(1)
neural network training
(1)
lottery ticket hypothesis
(1)
object detection
(1)
cross-lingual transfer
(1)
feature learning
(1)
in-context learning
(1)
conditional generation
(1)
neural network interpretability
(1)
multilingual nlp
(1)
Papers
Language Models are Few-shot Multilingual Learners
EMNLP 2021
Supermasks in Superposition
NIPS 2020
Plug and Play Language Models: A Simple Approach to Controlled Text Generation
ICLR 2020
Estimating Q(s,sā) with Deep Deterministic Dynamics Gradients
ICML 2020
LCA: Loss Change Allocation for Neural Network Training
NIPS 2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
NIPS 2019
Hamiltonian Neural Networks
NIPS 2019
Metropolis-Hastings Generative Adversarial Networks
ICML 2019
Faster Neural Networks Straight from JPEG
NIPS 2018
An intriguing failing of convolutional neural networks and the CoordConv solution
NIPS 2018
Measuring the Intrinsic Dimension of Objective Landscapes
ICLR 2018
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space
CVPR 2017
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
NIPS 2017
Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation
CVPR 2016
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
NIPS 2016
Deep Neural Networks Are Easily Fooled: High Confidence Predictions for Unrecognizable Images
CVPR 2015
Deep Generative Stochastic Networks Trainable by Backprop
ICML 2014
How transferable are features in deep neural networks?
NIPS 2014