Chris J Maddison
16 papers · 2013–2024 · 1 venue · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (48) 🏆 Keyword Champion
🧭
Keyword Pioneer
📈
Trend Setter
💎
Century Club · Bronze
🌈
Renaissance Researcher
(6)
🗃️
Keyword Collector
(102)
Venues
Top co-authors
Research topics
Machine Learning
(15)
Optimization & Theory
(12)
Deep Learning
(7)
Learning Types
(7)
Artificial Intelligence
(5)
Models
(5)
Mathematics & Optimization
(4)
Architectures
(3)
Bayesian & Probabilistic · Machine Learning
(3)
Core AI
(3)
Core Methods
(3)
Mathematics
(3)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Optimization
(2)
Probability
(2)
Keywords
latent variable model
(2)
generative model
(2)
variance reduction
(2)
continuous optimization
(2)
variational inference
(1)
convex optimization
(1)
learning theory
(1)
text mining
(1)
binary classification
(1)
attention mechanism
(1)
data augmentation
(1)
sample complexity
(1)
causal effect estimation
(1)
universal approximation
(1)
empirical risk minimization
(1)
natural language processing
(1)
gradient estimation
(1)
marginal likelihood
(1)
covariance matrix
(1)
variational inequality
(1)
Papers
End-To-End Causal Effect Estimation from Unstructured Natural Language Data
NeurIPS 2024
Observational Scaling Laws and the Predictability of Langauge Model Performance
NeurIPS 2024
On the Efficiency of ERM in Feature Learning
NeurIPS 2024
MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
NeurIPS 2023
Probabilistic Invariant Learning with Randomized Linear Classifiers
NeurIPS 2023
The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit
NeurIPS 2023
Learning Generalized Gumbel-max Causal Mechanisms
NeurIPS 2021
Lossy Compression for Lossless Prediction
NeurIPS 2021
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
NeurIPS 2020
Gradient Estimation with Stochastic Softmax Tricks
NeurIPS 2020
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
NeurIPS 2019
Hamiltonian descent for composite objectives
NeurIPS 2019
Filtering Variational Objectives
NeurIPS 2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
NeurIPS 2017
A* Sampling
NeurIPS 2014
Annealing between distributions by averaging moments
NeurIPS 2013