Lakshminarayanan, Balaji

Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

Lakshminarayanan, B., Pritzel, A., & Blundell, C. (2016) · arXiv

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 3,666

Clinically applicable deep learning for diagnosis and referral in retinal disease

De Fauw, J., Ledsam, J. R., Romera-Paredes, B., Nikolov, S., Tomasev, N., Blackwell, S., Askham, H., Glorot, X., O’Donoghue, B., Visentin, D., et al. (2018) · Nature Medicine

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 2,639

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift

Ovadia, Y., Fertig, E., Ren, J., Nado, Z., Sculley, D., Nowozin, S., Dillon, J. V., Lakshminarayanan, B., & Snoek, J. (2019) · arXiv

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 989

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

Simple and principled uncertainty estimation with deterministic deep learning via distance awareness

Liu, J. Z., Lin, Z., Padhy, S., Tran, D., Bedrax-Weiss, T., & Lakshminarayanan, B. (2020) · arXiv

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 237

The Cramer Distance as a Solution to Biased Wasserstein Gradients

Bellemare, M. G., Danihelka, I., Dabney, W., Mohamed, S., Lakshminarayanan, B., Hoyer, S., & Munos, R. (2017) · arXiv

Generative Adversarial Networks and Image SynthesisGeometric Analysis and Curvature Flows

Cited by 223

Exploring the Limits of Out-of-Distribution Detection

Fort, S., Ren, J., & Lakshminarayanan, B. (2021) · arXiv

Adversarial Robustness in Machine LearningAnomaly Detection Techniques and Applications

Cited by 142

Does your dermatology classifier know what it doesn’t know? Detecting the long-tail of unseen conditions

Guha Roy, A., Ren, J., Azizi, S., Loh, A., Natarajan, V., Mustafa, B., Pawlowski, N., Freyberg, J., Liu, Y., Beaver, Z., et al. (2022) · Medical Image Analysis

Anomaly Detection Techniques and ApplicationsCutaneous Melanoma Detection and Management

Cited by 77

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

Bayesian Deep Ensembles via the Neural Tangent Kernel

He, B., Lakshminarayanan, B., & Teh, Y. W. (2020) · arXiv

Gaussian Processes and Bayesian InferenceAdversarial Robustness in Machine Learning

Cited by 36

Combining Ensembles and Data Augmentation can Harm your Calibration

Wen, Y., Jerfel, G., Muller, R., Dusenberry, M. W., Snoek, J., Lakshminarayanan, B., & Tran, D. (2020) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 27

Self-Evaluation Improves Selective Generation in Large Language Models

Ren, J., Zhao, Y., Vu, T., Liu, P. J., & Lakshminarayanan, B. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 5