Lars Buesing
18 papers · 2007–2022 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (46) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Gold 🐣 Hot Topic Early Bird
🧭
Keyword Pioneer
🧬
Topic Evolution
🌟
Keyword Trendsetter Combo
(4)
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
🌈
Renaissance Researcher
(5)
🗃️
Keyword Collector
(104)
📈
Trend Setter
Top co-authors
Research topics
Machine Learning
(13)
Artificial Intelligence
(11)
Core Methods
(10)
Core AI
(8)
Reinforcement Learning
(7)
Optimization & Theory
(7)
Deep Learning
(6)
Interdisciplinary
(6)
Bayesian & Probabilistic · Machine Learning
(6)
Science
(6)
Bayesian & Probabilistic · Artificial Intelligence
(5)
Learning Types
(5)
Methods
(5)
Architectures
(4)
Healthcare & Medicine
(3)
Keywords
value function
(4)
calcium imaging
(3)
neural population
(3)
variational inference
(3)
spiking neuron
(3)
credit assignment
(2)
variational autoencoder
(2)
model-based rl
(2)
expectation maximization
(2)
dynamical system
(2)
dimensionality reduction
(2)
bayesian inference
(2)
counterfactual reasoning
(2)
model-free reinforcement learning
(2)
monte carlo tree search
(2)
model-based reinforcement learning
(2)
variance reduction
(2)
latent variable model
(2)
generalized linear model
(2)
information bottleneck
(1)
Papers
Making Sense of Raw Input (Extended Abstract)
IJCAI 2022
Counterfactual Credit Assignment in Model-Free Reinforcement Learning
ICML 2021
Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions
AISTATS 2020
Combining Q-Learning and Search with Amortized Value Estimates
ICLR 2020
Pointer Graph Networks
NeurIPS 2020
Value-driven Hindsight Modelling
NeurIPS 2020
Credit Assignment Techniques in Stochastic Computation Graphs
AISTATS 2019
Temporal Difference Variational Auto-Encoder
ICLR 2019
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
ICLR 2019
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders
NeurIPS 2017
Imagination-Augmented Agents for Deep Reinforcement Learning
NeurIPS 2017
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)
NeurIPS 2015
Clustered factor analysis of multineuronal spike data
NeurIPS 2014
Inferring neural population dynamics from multiple partial recordings of the same neural circuit
NeurIPS 2013
Spectral learning of linear dynamics from generalised-linear observations with application to neural population data
NeurIPS 2012
Empirical models of spiking in neural populations
NeurIPS 2011
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
NeurIPS 2008
Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons
NeurIPS 2007