Salimans, Tim

Improved Techniques for Training GANs

Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., & Chen, X. (2016) · arXiv

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 6,965

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E., Ghasemipour, S. K. S., Ayan, B. K., Mahdavi, S. S., Lopes, R. G., et al. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 2,528

Image Super-Resolution Via Iterative Refinement

Saharia, C., Ho, J., Chan, W., Salimans, T., Fleet, D. J., & Norouzi, M. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Image Processing TechniquesGenerative Adversarial Networks and Image Synthesis

Cited by 1,829

Image Super-Resolution via Iterative Refinement

Saharia, C., Ho, J., Chan, W., Salimans, T., Fleet, D. J., & Norouzi, M. (2021) · arXiv

Advanced Image Processing TechniquesGenerative Adversarial Networks and Image Synthesis

Cited by 1,829

Palette: Image-to-Image Diffusion Models

Saharia, C., Chan, W., Chang, H., Lee, C., Ho, J., Salimans, T., Fleet, D., & Norouzi, M. (2022) · Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 1,717

Classifier-Free Diffusion Guidance

Ho, J., & Salimans, T. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine Learning

Cited by 1,126

Dota 2 with Large Scale Deep Reinforcement Learning

OpenAI, :, Berner, C., Brockman, G., Chan, B., Cheung, V., Dębiak, P., Dennison, C., Farhi, D., Fischer, Q., et al. (2019) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 1,065

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Salimans, T., Ho, J., Chen, X., Sidor, S., & Sutskever, I. (2017) · arXiv

Reinforcement Learning in RoboticsEvolutionary Algorithms and Applications

Cited by 1,027

PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications

Salimans, T., Karpathy, A., Chen, X., & Kingma, D. P. (2017) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 584

Photorealistic Text-To-Image Diffusion Models with Deep Language Understanding

Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E., Ghasemipour, K., Lopes, R. G., Ayan, B. K., Salimans, T., et al. (2022) · Advances in Neural Information Processing Systems 35

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 559

Cascaded Diffusion Models for High Fidelity Image Generation

Ho, J., Saharia, C., Chan, W., Fleet, D. J., Norouzi, M., & Salimans, T. (2021) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 514

Imagen Video: High Definition Video Generation with Diffusion Models

Ho, J., Chan, W., Saharia, C., Whang, J., Gao, R., Gritsenko, A., Kingma, D. P., Poole, B., Norouzi, M., Fleet, D. J., et al. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 399

Variational Diffusion Models

Kingma, D. P., Salimans, T., Poole, B., & Ho, J. (2021) · arXiv

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 374

Axial Attention in Multidimensional Transformers

Ho, J., Kalchbrenner, N., Weissenborn, D., & Salimans, T. (2019) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 370

Video Diffusion Models

Ho, J., Salimans, T., Gritsenko, A., Chan, W., Norouzi, M., & Fleet, D. J. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 301

Progressive Distillation for Fast Sampling of Diffusion Models

Salimans, T., & Ho, J. (2022) · arXiv

Generative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine Learning

Cited by 287

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion

Hoogeboom, E., Mensink, T., Heek, J., Lamerigts, K., Gao, R., & Salimans, T. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 0