Secondmind

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Secondmind exists to help automotive engineers design better cars faster. The company’s cloud-native software, powered by Secondmind Active Learning, address...

Latest Videos

Linear combinations of latents in generative models subspaces and beyond

Rethinking the use of VAEs in Bayesian optimisation over structured spaces

Yuko Kuroki - Advancing sequential decision-making

Andreas Bender - AI in drug discovery

What is Secondmind for Design Space Exploration

What is Secondmind for Calibration

Who is Secondmind

Ilija Bogunovic - From Data to Confident Decisions Robust and Efficient Algorithmic Decision Making

Mickael Binois - Leveraging replication in active learning

Dario Azzimonti - Preference learning with Gaussian processes

Mojmír Mutný - Optimal Experiment Design in Markov Chains

Domenic Di Francesco - Data-Centric Engineering for Coherent Risk Management

Antonio Del Rio Chanona - Multi-Fidelity Bayesian Optimization in Chemical Engineering

Luigi Nardi - Harnessing new information in Bayesian optimization

Christopher Nemeth - Coin Sampling Gradient-Based Bayesian Inference without Learning Rates

David Duvenaud - A farewell to GPs A roadmap for ultra-scalable simulation and inference in SPDEs

Ítalo Gomes Gonçalves - Variational Gaussian processes for spatial modeling the geoML project

Sebastian Farquhar - Unbiased Active Learning and Testing

Martin Jørgensen - Bézier Gaussian Processes

Pablo Moreno-Muñoz - Model Recycling with Gaussian Processes

Aryan Deshwal - Bayesian Optimization over Combinatorial Structures

Dino Sejdinovic - Developments at the Interface Between Kernel Embeddings and Gaussian Processes

François-Xavier Briol - Bayesian Estimation of Integrals A Multi-task Approach

François Bachoc - Sequential construction and dimension reduction of GP under inequality constraints

Frank Hutter - Towards Deep Learning 2.0 Going to the Meta-Level

Noémie Jaquier - Bayesian optimization on Riemannian manifolds for robot learning

Roberto Calandra - Bayesian optimization for robotics

Emtiyaz Khan - Bayesian Principles for Machine Learning

José Miguel Hernández-Lobato - Probabilistic Methods for Increased Robustness in Machine Learning

Carl Henrik Ek - Modulating surrogates for bayesian optimization