Mohammad Emtiyaz Khan
34 papers · 2009–2025 · 8 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 14 separate collaboration groups - the largest holds only 35% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Mohammad Emtiyaz Khan?
6 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Thomas Möllenhoff, Siddharth Swaroop, Alexander Immer
12 papers
· 2019–2025
· NeurIPS, ICLR, ICML
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Connecting Federated ADMM to Bayes
ICLR 2025
Conformal Prediction via Regression-as-Classification
ICLR 2024
Model Merging by Uncertainty-Based Gradient Matching
ICLR 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
ICML 2024
Variational Learning is Effective for Large Deep Networks
ICML 2024
Exploiting Inferential Structure in Neural Processes
UAI 2023
SAM as an Optimal Relaxation of Bayes
ICLR 2023
The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data
NeurIPS 2023
Knowledge-Adaptation Priors
NeurIPS 2021
Continual Deep Learning by Functional Regularisation of Memorable Past
NeurIPS 2020
Approximate Inference Turns Deep Networks into Gaussian Processes
NeurIPS 2019
Practical Deep Learning with Bayesian Principles
NeurIPS 2019
8 papers whose co-authors appear nowhere else under this name
The Bayesian Learning Rule
JMLR 2023
The Lie-Group Bayesian Learning Rule
AISTATS 2023
Subset-of-data variational inference for deep Gaussian-processes regression
UAI 2021
Training Binary Neural Networks using the Bayesian Learning Rule
ICML 2020
A Generalization Bound for Online Variational Inference
ACML 2019
Scalable Training of Inference Networks for Gaussian-Process Models
ICML 2019
Kullback-Leibler Proximal Variational Inference
NeurIPS 2015
Decoupled Variational Gaussian Inference
NeurIPS 2014