Machine Learning Reading Group @ CUED
Reading Group in Division F of the Cambridge University Engineering Department. Run by Zoubin Ghahramani and Carl Rasmussen.
This reading group is also called 5CF6: Machine Learning Research and Communication Club.
Contact: Zoubin Ghahramani ; Carl Edward Rasmussen ; Dr R.E. Turner ; Andy Lin ; Isaac Reid ; Xianda Sun ; Yichao Liang ; 120952 ; 121990
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Statistics Clinic Summer 2025 II
The structure of curvature in neural networks
Vision-language models (VLMs)
Vision-language models (VLMs)
Evaluating and Regulating Foundation Models
Out-of-context reasoning/learning in LLMs and its safety implications
Learning to See the World in 3D
An Introduction to In-Context Learning
ML for Medium-Range Weather Forecasting
Influence Functions
Sampling with diffusion models
Geometric Deep Learning for Structure-Based Drug Design
Diffusion Models Beyond Mean Prediction
Unpacking UKβs New AI Action Plan: Ambition versus Reality
An Introduction to Algorithmic Differentiation
An Introduction to Algorithmic Differentiation
Learning curve prediction for AutoML
Learning curve prediction for AutoML
Natural Experiments in NLP and Where to Find Them
Task Alignment
A Light Introduction to Topological Data Analysis
Mean Field Theory of NNs
Discussing the Stanford AI Report
Discussing the Stanford AI Report
AI Control
Neural likelihood-free inference
An Introduction to the Conjugate Gradient Method
An Introduction to Transformer Neural Processes
Learning Symmetries in Neural Networks
GenCast: Diffusion-based ensemble forecasting for medium-range weather (or: How to ruin a numerical weather forecasterβs Christmas)
Bayesian coresets
Flow matching, stochastic interpolants and everything in between
Challenges of Regulating Increasingly Complicated Human-AI Collaborative Systems
A Poisson Process Model for Monte Carlo
Learning Directed Acyclic Graphs (DAGs) With Continuous Optimization
Deep Learning for Medium-Range Global Weather Prediction
Learning linear models in-context with transformers
Deciphering Batch Effects in Single-cell Transcriptomics with Concept Bottlenecks
SchrΓΆdinger bridges, diffusion and SDEs
The LLM Tidal Wave
The LLM Tidal Wave
Game theory, distributional reinforcement learning, control and verification
On choosing the mass matrix for Hamiltonian Monte Carlo
Reward Modelling
Navigating the Future: Upcoming EU AI Regulation and its Potential Impact on the Field
Learning-based multiscale modeling: computing, data science, and uncertainty quantification
Neural Tangent Kernel
No-regret Dynamics for Multi-agent Learning
Scalable Approaches to Self-Supervised Learning using Spectral Analysis
Physics-informed machine learning
Causal Machine Learning
User Manipulation in Recommender Systems
Random Features for Kernel Approximation
An Overview of Differential Privacy, Membership Inference Attacks, and Federated Learning
Bayesian Neural Networks
Offline Reinforcement Learning
{PF}^2ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization Under Unknown Constraints
Information Geometry β Natural Gradient Descent
Predicting generalization of ML models.
Deep Learning Book - Meeting 9 - Representation Learning
Deep Learning Book - Meeting 8 - Autoencoders
Deep Learning Book - Meeting 7 - Neural Turing Machines & Conditional Random Fields as RNNs
Deep Learning Book - Meeting 6 - Recurrent Neural Networks
Deep Learning Book - Meeting 5 - ResNets and DenseNets
Deep Learning Book - Meeting 4 - Convolutional Networks
Deep Learning Book - Meeting 3 - Optimization
Deep Learning Book - Meeting 2 - Regularization
Deep Learning Book - Meeting 1 - Deep Feedforward NNs
It's the Network Dummy: Exhuming the reticular theory while shoveling a little dirt on the neuron doctrine
Differentiable Data Structures and (if we have time) POMDPs
Model selection in a large compositional space
Information bottleneck
Cancelled: No RCC
Redirected to Rob Nowak, LR12
Information Retrieval
Numerical Linear Algebra
Cancelled
Cancelled
(Canceled) A Causal Calculus for Statistical Research
Message Passing
Divergence measures and message passing - CANCELLED
CANCELLED
Sensible priors from finite linear models
Affinity Propagation and Hierarchical Beta Processes
Change Point Problems in Linear Dynamical Systems
Active Learning and Experimental Design
Please see above for contact details for this list.
![[Talks.cam]](/static/images/talkslogosmall.gif)

Abbas Mammadov (University of Oxford).
Tuesday 24 March 2026, 15:00-16:30