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Jason Yosinski

18 papers · 2014–2021 · 5 conferences · across top CS/AI conferences

Achievements

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+12 more ↓ šŸƒ Academic Marathon (7) šŸŒ Conference Polyglot (5) šŸŒ‰ Interdisciplinary Bridge šŸ§­ Keyword Pioneer šŸ£ Hot Topic Early Bird
šŸ§­ Keyword Pioneer šŸ£ Hot Topic Early Bird šŸŒ Conference Polyglot (5) šŸŒŸ Keyword Trendsetter Combo (6) šŸ§¬ Topic Evolution šŸ‘‘ Triple Crown šŸ“ˆ Trend Setter šŸš€ Conference Pioneer šŸ—ƒļø Keyword Collector (82) šŸ”„ Unstoppable (8) ā“ The Questioner šŸ’Ž Century Club (18)

Conferences

NIPS (9) CVPR (3) ICML (3) ICLR (2) EMNLP (1)

Top co-authors

Rosanne Liu (9) Jeff Clune (4) Jane Hung (3) Eric Frank (3) Anh Nguyen (3) Janice Lan (3) Yoshua Bengio (3) Piero Molino (2) Andrea Madotto (2) Alexey Dosovitskiy (2)

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