Mohammad Norouzi

Affiliations:
  • Google Brain, Mountain View, CA, USA
  • University of Toronto, Computer Science Department, Canada (PhD 2015)


According to our database1, Mohammad Norouzi authored at least 93 papers between 2009 and 2023.

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Bibliography

2023
Image Super-Resolution via Iterative Refinement.
IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

Synthetic Data from Diffusion Models Improves ImageNet Classification.
Trans. Mach. Learn. Res., 2023

Monocular Depth Estimation using Diffusion Models.
CoRR, 2023

The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Novel View Synthesis with Diffusion Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

TryOnDiffusion: A Tale of Two UNets.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Character-Aware Models Improve Visual Text Rendering.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Decoder Denoising Pretraining for Semantic Segmentation.
Trans. Mach. Learn. Res., 2022

Generate, Annotate, and Learn: NLP with Synthetic Text.
Trans. Assoc. Comput. Linguistics, 2022

Cascaded Diffusion Models for High Fidelity Image Generation.
J. Mach. Learn. Res., 2022

Imagen Video: High Definition Video Generation with Diffusion Models.
CoRR, 2022

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.
CoRR, 2022

Robust and Efficient Medical Imaging with Self-Supervision.
CoRR, 2022

Palette: Image-to-Image Diffusion Models.
Proceedings of the SIGGRAPH '22: Special Interest Group on Computer Graphics and Interactive Techniques Conference, Vancouver, BC, Canada, August 7, 2022

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Video Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Learning Fast Weight Language Models.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Denoising Pretraining for Semantic Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Generate, Annotate, and Learn: Generative Models Advance Self-Training and Knowledge Distillation.
CoRR, 2021

Learning to Efficiently Sample from Diffusion Probabilistic Models.
CoRR, 2021

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization.
CoRR, 2021

SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network.
CoRR, 2021

Why Do Better Loss Functions Lead to Less Transferable Features?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization.
Proceedings of the 9th International Conference on Learning Representations, 2021

Mastering Atari with Discrete World Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

No MCMC for me: Amortized sampling for fast and stable training of energy-based models.
Proceedings of the 9th International Conference on Learning Representations, 2021

Benchmarks for Deep Off-Policy Evaluation.
Proceedings of the 9th International Conference on Learning Representations, 2021

WaveGrad: Estimating Gradients for Waveform Generation.
Proceedings of the 9th International Conference on Learning Representations, 2021

Big Self-Supervised Models Advance Medical Image Classification.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
What's in a Loss Function for Image Classification?
CoRR, 2020

RL Unplugged: Benchmarks for Offline Reinforcement Learning.
CoRR, 2020

NiLBS: Neural Inverse Linear Blend Skinning.
CoRR, 2020

Exemplar VAEs for Exemplar based Generation and Data Augmentation.
CoRR, 2020

Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Big Self-Supervised Models are Strong Semi-Supervised Learners.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Simple Framework for Contrastive Learning of Visual Representations.
Proceedings of the 37th International Conference on Machine Learning, 2020

Imputer: Sequence Modelling via Imputation and Dynamic Programming.
Proceedings of the 37th International Conference on Machine Learning, 2020

An Optimistic Perspective on Offline Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models.
Proceedings of the 8th International Conference on Learning Representations, 2020

Dream to Control: Learning Behaviors by Latent Imagination.
Proceedings of the 8th International Conference on Learning Representations, 2020

Your classifier is secretly an energy based model and you should treat it like one.
Proceedings of the 8th International Conference on Learning Representations, 2020

Non-Autoregressive Machine Translation with Latent Alignments.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

NASA Neural Articulated Shape Approximation.
Proceedings of the Computer Vision - ECCV 2020, 2020

Dynamic Programming Encoding for Subword Segmentation in Neural Machine Translation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
NASA: Neural Articulated Shape Approximation.
CoRR, 2019

Efficient Exploration with Self-Imitation Learning via Trajectory-Conditioned Policy.
CoRR, 2019

Striving for Simplicity in Off-policy Deep Reinforcement Learning.
CoRR, 2019

Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Similarity of Neural Network Representations Revisited.
Proceedings of the 36th International Conference on Machine Learning, 2019

Understanding the Impact of Entropy on Policy Optimization.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning to Generalize from Sparse and Underspecified Rewards.
Proceedings of the 36th International Conference on Machine Learning, 2019

Optimal Completion Distillation for Sequence Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Understanding Posterior Collapse in Generative Latent Variable Models.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Contingency-Aware Exploration in Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Memory Augmented Policy Optimization for Program Synthesis with Generalization.
CoRR, 2018

Parallel Architecture and Hyperparameter Search via Successive Halving and Classification.
CoRR, 2018

Neural Program Synthesis with Priority Queue Training.
CoRR, 2018

Embedding Text in Hyperbolic Spaces.
Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing, 2018

Discovery of Latent 3D Keypoints via End-to-end Geometric Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Smoothed Action Value Functions for Learning Gaussian Policies.
Proceedings of the 35th International Conference on Machine Learning, 2018

QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension.
Proceedings of the 6th International Conference on Learning Representations, 2018

Trust-PCL: An Off-Policy Trust Region Method for Continuous Control.
Proceedings of the 6th International Conference on Learning Representations, 2018

The Importance of Generation Order in Language Modeling.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Sequence to Sequence Mixture Model for Diverse Machine Translation.
Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018

2017
Detecting Cancer Metastases on Gigapixel Pathology Images.
CoRR, 2017

N-gram Language Modeling using Recurrent Neural Network Estimation.
CoRR, 2017

Bridging the Gap Between Value and Policy Based Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Filtering Variational Objectives.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Device Placement Optimization with Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs.
Proceedings of the 34th International Conference on Machine Learning, 2017

Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders.
Proceedings of the 34th International Conference on Machine Learning, 2017

Improving Policy Gradient by Exploring Under-appreciated Rewards.
Proceedings of the 5th International Conference on Learning Representations, 2017

Neural Combinatorial Optimization with Reinforcement Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

Pixel Recursive Super Resolution.
Proceedings of the IEEE International Conference on Computer Vision, 2017

PixColor: Pixel Recursive Colorization.
Proceedings of the British Machine Vision Conference 2017, 2017

2016
Compact Discrete Representations for Scalable Similarity Search.
PhD thesis, 2016

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.
CoRR, 2016

Reward Augmented Maximum Likelihood for Neural Structured Prediction.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
CO2 Forest: Improved Random Forest by Continuous Optimization of Oblique Splits.
CoRR, 2015

Efficient Non-greedy Optimization of Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Fast Exact Search in Hamming Space With Multi-Index Hashing.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Zero-Shot Learning by Convex Combination of Semantic Embeddings.
Proceedings of the 2nd International Conference on Learning Representations, 2014

2013
Cartesian K-Means.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Hamming Distance Metric Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Fast search in Hamming space with multi-index hashing.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Minimal Loss Hashing for Compact Binary Codes.
Proceedings of the 28th International Conference on Machine Learning, 2011

2009
Stacks of convolutional Restricted Boltzmann Machines for shift-invariant feature learning.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009


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