Devansh Arpit
16 papers · 2014–2024 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (26) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Mega-Team Β· Squad
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Triple Crown
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Keyword Pioneer
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Conference Pioneer
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Unstoppable Β· Bronze
β
The Questioner
(2)
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Century Club Β· Bronze
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Trend Setter
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Keyword Collector
(72)
Top co-authors
Research topics
Machine Learning
(14)
Optimization & Theory
(12)
Deep Learning
(9)
Techniques
(5)
Architectures
(4)
Learning Types
(4)
Artificial Intelligence
(3)
Core AI
(3)
Core Methods
(3)
Application Areas
(2)
Data Science & Analytics
(1)
Knowledge & Reasoning
(1)
Mathematics & Optimization
(1)
Mathematics
(1)
Methods
(1)
Keywords
batch normalization
(3)
residual network
(2)
learning rate
(2)
stochastic gradient descent
(2)
causal discovery
(2)
representation learning
(2)
subspace learning
(1)
feature extraction
(1)
adversarial robustness
(1)
ensemble learning
(1)
anomaly detection
(1)
policy gradient
(1)
sequence modeling
(1)
manifold learning
(1)
sparse representation
(1)
domain generalization
(1)
language modeling
(1)
fourier analysis
(1)
distributed computing
(1)
learning theory
(1)
Papers
Causal Layering via Conditional Entropy
CLeaR 2024
On the Unlikelihood of D-Separation
PGM 2024
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
ICLR 2024
Merlion: End-to-End Machine Learning for Time Series
JMLR 2023
Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
NeurIPS 2022
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization
ICML 2021
The Break-Even Point on Optimization Trajectories of Deep Neural Networks
ICLR 2020
h-detach: Modifying the LSTM Gradient Towards Better Optimization
ICLR 2019
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets
NeurIPS 2019
On the Spectral Bias of Neural Networks
ICML 2019
Fraternal Dropout
ICLR 2018
Residual Connections Encourage Iterative Inference
ICLR 2018
A Closer Look at Memorization in Deep Networks
ICML 2017
Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks
ICML 2016
Why Regularized Auto-Encoders learn Sparse Representation?
ICML 2016
Dimensionality Reduction with Subspace Structure Preservation
NeurIPS 2014