151 Diffusion Models in Python, a Live Demo with Jonas Arruda

151 Diffusion Models in Python, a Live Demo with Jonas Arruda

#150 Fast Bayesian Deep Learning, with David Rügamer, Emanuel Sommer & Jakob Robnik

#150 Fast Bayesian Deep Learning, with David Rügamer, Emanuel Sommer & Jakob Robnik

BITESIZE | Building Resilience in Modern Tech Careers

BITESIZE | Building Resilience in Modern Tech Careers

#149 The Future of Work in Tech, with Alana Karen

#149 The Future of Work in Tech, with Alana Karen

BITESIZE | The Trial Design That Learns in Real Time

BITESIZE | The Trial Design That Learns in Real Time

#148 Adaptive Trials, Bayesian Thinking, and Learning from Data, with Scott Berry

#148 Adaptive Trials, Bayesian Thinking, and Learning from Data, with Scott Berry

BITESIZE | Making Variational Inference Reliable: From ADVI to DADVI

BITESIZE | Making Variational Inference Reliable: From ADVI to DADVI

#147 Fast Approximate Inference without Convergence Worries, with Martin Ingram

#147 Fast Approximate Inference without Convergence Worries, with Martin Ingram

BITESIZE | Why Bayesian Stats Matter When the Physics Gets Extreme

BITESIZE | Why Bayesian Stats Matter When the Physics Gets Extreme

#146 Lasers, Planets, and Bayesian Inference, with Ethan Smith

#146 Lasers, Planets, and Bayesian Inference, with Ethan Smith

BITESIZE | How to Thrive in an AI-Driven Workplace?

BITESIZE | How to Thrive in an AI-Driven Workplace?

#145 Career Advice in the Age of AI, with Jordan Thibodeau

#145 Career Advice in the Age of AI, with Jordan Thibodeau

Try Monte Carlo dropout, The simplest Bayesian deep learning trick that works

BITESIZE | Why is Bayesian Deep Learning so Powerful?

BITESIZE | Why is Bayesian Deep Learning so Powerful?

#144 Why is Bayesian Deep Learning so Powerful, with Maurizio Filippone

#144 Why is Bayesian Deep Learning so Powerful, with Maurizio Filippone

BITESIZE | Are Bayesian Models the Missing Ingredient in Nutrition Research?

BITESIZE | Are Bayesian Models the Missing Ingredient in Nutrition Research?

#143 Transforming Nutrition Science with Bayesian Methods, with Christoph Bamberg

#143 Transforming Nutrition Science with Bayesian Methods, with Christoph Bamberg

BITESIZE | How Bayesian Additive Regression Trees Work in Practice

BITESIZE | How Bayesian Additive Regression Trees Work in Practice

#142 Bayesian Trees & Deep Learning for Optimization & Big Data, with Gabriel Stechschulte

#142 Bayesian Trees & Deep Learning for Optimization & Big Data, with Gabriel Stechschulte

BITESIZE | How Probability Becomes Causality?

BITESIZE | How Probability Becomes Causality?

#141 AI Assisted Causal Inference, with Sam Witty

#141 AI Assisted Causal Inference, with Sam Witty

BITESIZE | How to Think Causally About Your Models?

BITESIZE | How to Think Causally About Your Models?

#140 NFL Analytics & Teaching Bayesian Stats, with Ron Yurko

#140 NFL Analytics & Teaching Bayesian Stats, with Ron Yurko

BITESIZE | Is Bayesian Optimization the Answer?

BITESIZE | Is Bayesian Optimization the Answer?

#139 Efficient Bayesian Optimization in PyTorch, with Max Balandat

#139 Efficient Bayesian Optimization in PyTorch, with Max Balandat

BITESIZE | What's Missing in Bayesian Deep Learning?

BITESIZE | What's Missing in Bayesian Deep Learning?

#138 Quantifying Uncertainty in Bayesian Deep Learning, Live from Imperial College London

#138 Quantifying Uncertainty in Bayesian Deep Learning, Live from Imperial College London

BITESIZE | Practical Applications of Causal AI with LLMs, with Robert Ness

BITESIZE | Practical Applications of Causal AI with LLMs, with Robert Ness

#137 Causal AI & Generative Models, with Robert Ness

#137 Causal AI & Generative Models, with Robert Ness

BITESIZE | How to Make Your Models Faster, with Haavard Rue & Janet van Niekerk

BITESIZE | How to Make Your Models Faster, with Haavard Rue & Janet van Niekerk

#136 Bayesian Inference at Scale: Unveiling INLA, with Haavard Rue & Janet van Niekerk