← Authors

Dumitru Erhan

20 papers · 2010–2023 · 6 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (13) 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (35) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🧬 Topic Evolution 🌱 Topic Pioneer πŸ—ƒοΈ Keyword Collector (67) πŸš€ Conference Pioneer πŸ’Ž Century Club (20) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter ❓ The Questioner (2)

Conferences

ICLR (6) CVPR (5) NIPS (5) AISTATS (2) ICML (1) JMLR (1)

Top co-authors

Mohammad Babaeizadeh (6) Sergey Levine (4) Ruben Villegas (4) Pieter-jan Kindermans (4) Yoshua Bengio (3) Alexander Toshev (3) Chelsea Finn (3) Dragomir Anguelov (3) Christian Szegedy (3) Dilip Krishnan (2)

Keywords

deep learning (5) deep neural network (4) image classification (3) object detection (3) unsupervised learning (3) convolutional neural network (3) feature learning (2) video prediction (2) neural network (2) representation learning (2) domain adaptation (2) unsupervised pre-training (2) deep belief network (2) image captioning (1) natural language generation (1) video generation (1) multi-task learning (1) video understanding (1) computer vision (1) image reconstruction (1)

Papers

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization NIPS 2023
Phenaki: Variable Length Video Generation from Open Domain Textual Descriptions ICLR 2023
Information Prioritization through Empowerment in Visual Model-based RL ICLR 2022
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation ICLR 2020
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving CVPR 2020
Model Based Reinforcement Learning for Atari ICLR 2020
A Benchmark for Interpretability Methods in Deep Neural Networks NIPS 2019
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks NIPS 2019
Hierarchical Long-term Video Prediction without Supervision ICML 2018
Stochastic Variational Video Prediction ICLR 2018
Learning how to explain neural networks: PatternNet and PatternAttribution ICLR 2018
Unsupervised Pixel-Level Domain Adaptation With Generative Adversarial Networks CVPR 2017
Domain Separation Networks NIPS 2016
Going Deeper With Convolutions CVPR 2015
Show and Tell: A Neural Image Caption Generator CVPR 2015
Scalable Object Detection using Deep Neural Networks CVPR 2014
Deep Neural Networks for Object Detection NIPS 2013
Deep Learners Benefit More from Out-of-Distribution Examples AISTATS 2011
Why Does Unsupervised Pre-training Help Deep Learning? AISTATS 2010
Why Does Unsupervised Pre-training Help Deep Learning? JMLR 2010