Neitz, Alexander

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

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

A Simulation-Based Architecture for Smart Cyber-Physical Systems

Gabor, T., Belzner, L., Kiermeier, M., Beck, M. T., & Neitz, A. (2016) · 2016 IEEE International Conference on Autonomic Computing (ICAC)

Digital Transformation in IndustryModeling and Simulation Systems

Cited by 298

OpenAI o1 System Card

OpenAI, :, Jaech, A., Kalai, A., Lerer, A., Richardson, A., El-Kishky, A., Low, A., Helyar, A., Madry, A., et al. (2024) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 50

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ahmed, O., Träuble, F., Goyal, A., Neitz, A., Bengio, Y., Schölkopf, B., Wüthrich, M., & Bauer, S. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 50