David Klindt
10 papers · 2017–2026 · 4 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (28) 💎 Century Club · Bronze
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Machine Learning
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Artificial Intelligence
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Deep Learning
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Core AI
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Optimization & Theory
(5)
Learning Types · Deep Learning
(4)
Learning Types · Machine Learning
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(2)
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Natural Language Processing
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sparse autoencoder
(2)
representation learning
(2)
system identification
(2)
adversarial learning
(1)
domain adaptation
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independent component analysis
(1)
adversarial optimization
(1)
visual cortex
(1)
interpretability
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sample complexity
(1)
neural network interpretability
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model analysis
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compositional generalization
(1)
biophysical modeling
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gradient descent
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sparse coding
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biomedical imaging
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learning rate
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receptive field
(1)
feature learning
(1)
Papers
Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalization
UAI 2026
Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders
ICML 2025
Cross-Entropy Is All You Need To Invert the Data Generating Process
ICLR 2025
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
ICML 2025
Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning
NeurIPS 2024
Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems
NeurIPS 2024
Measuring Per-Unit Interpretability at Scale Without Humans
NeurIPS 2024
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience
NeurIPS 2021
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
NeurIPS 2020
Neural system identification for large populations separating “what” and “where”
NeurIPS 2017