Jason Yosinski

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

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Achievements

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🗺️ Taxonomy Completionist (50) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

👑 Triple Crown 🌟 Keyword Trendsetter Combo (9) 🧬 Topic Evolution 🏆 Keyword Champion 🧭 Keyword Pioneer ❓ The Questioner 💎 Century Club · Bronze 🚀 Conference Pioneer 🔥 Unstoppable · Bronze 🗃️ Keyword Collector (93) 📈 Trend Setter

Venues

NeurIPS (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)

Research topics

Deep Learning (16) Machine Learning (14) Optimization & Theory · Machine Learning (10) Artificial Intelligence (8) Learning Types · Deep Learning (8) Architectures (7) Core AI · Artificial Intelligence (6) Optimization & Theory · Deep Learning (5) Techniques (5) Computer Vision (4) Core AI · Computer Vision (4) Core Methods (4) Learning Types · Machine Learning (4) Application Areas (3) Models (3)

Keywords

convolutional neural network (4) image generation (3) neural network (3) neural network pruning (2) deep neural network (2) image classification (2) representation learning (2) activation maximization (2) gradient-based optimization (1) transfer learning (1) continual learning (1) few-shot learning (1) neural network training (1) object detection (1) lottery ticket hypothesis (1) conditional generation (1) cross-lingual transfer (1) feature learning (1) neural network interpretability (1) in-context learning (1)

Papers

Language Models are Few-shot Multilingual Learners EMNLP 2021 Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients ICML 2020 Plug and Play Language Models: A Simple Approach to Controlled Text Generation ICLR 2020 Supermasks in Superposition NeurIPS 2020 Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask NeurIPS 2019 Hamiltonian Neural Networks NeurIPS 2019 LCA: Loss Change Allocation for Neural Network Training NeurIPS 2019 Metropolis-Hastings Generative Adversarial Networks ICML 2019 An intriguing failing of convolutional neural networks and the CoordConv solution NeurIPS 2018 Faster Neural Networks Straight from JPEG NeurIPS 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 NeurIPS 2017 Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation CVPR 2016 Synthesizing the preferred inputs for neurons in neural networks via deep generator networks NeurIPS 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? NeurIPS 2014