Randall Balestriero
33 papers · 2018–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (6) π Academic Marathon (7) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (11)
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Conference Polyglot
(6)
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Academic Marathon
(7)
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(10)
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Triple Crown
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Topic Evolution
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Trend Setter
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Prolific Year
(8)
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Century Club
(33)
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Keyword Collector
(95)
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Conferences
ICLR (9)
ICML (9)
NIPS (9)
ICCV (3)
CVPR (2)
MICCAI (1)
Top co-authors
Keywords
representation learning
(6)
self-supervised learning
(6)
data augmentation
(4)
deep network
(3)
network geometry
(2)
decision boundary
(2)
max-affine spline operator
(2)
contrastive learning
(2)
feature learning
(1)
unified benchmark
(1)
image classification
(1)
model evaluation
(1)
multimodal learning
(1)
multi-modal learning
(1)
class imbalance
(1)
manifold learning
(1)
time-frequency analysis
(1)
network visualization
(1)
probabilistic modeling
(1)
visual representation
(1)
Papers
$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
ICLR 2025
Beyond [cls]: Exploring the True Potential of Masked Image Modeling Representations
ICCV 2025
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
ICML 2025
MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES
ICML 2025
Cross-Entropy Is All You Need To Invert the Data Generating Process
ICLR 2025
General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound
MICCAI 2025
No Location Left Behind: Measuring and Improving the Fairness of Implicit Representations for Earth Data
ICLR 2025
From Linearity to Non-Linearity: How Masked Autoencoders Capture Spatial Correlations
ICCV 2025
Deep Networks Always Grok and Here is Why
ICML 2024
UniBench: Visual Reasoning Requires Rethinking Vision-Language Beyond Scaling
NIPS 2024
How Learning by Reconstruction Produces Uninformative Features For Perception
ICML 2024
Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation
ICML 2024
The SSL Interplay: Augmentations, Inductive Bias, and Generalization
ICML 2023
Understanding the detrimental class-level effects of data augmentation
NIPS 2023
An Information Theory Perspective on Variance-Invariance-Covariance Regularization
NIPS 2023
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries
CVPR 2023
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need
ICCV 2023
The hidden uniform cluster prior in self-supervised learning
ICLR 2023
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
ICLR 2023
RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank
ICML 2023
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values
CVPR 2022
The Effects of Regularization and Data Augmentation are Class Dependent
NIPS 2022
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods
NIPS 2022
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining
ICLR 2022
A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training
NIPS 2022
projUNN: efficient method for training deep networks with unitary matrices
NIPS 2022
The Recurrent Neural Tangent Kernel
ICLR 2021
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks
NIPS 2020
The Geometry of Deep Networks: Power Diagram Subdivision
NIPS 2019
From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference
ICLR 2019
A Max-Affine Spline Perspective of Recurrent Neural Networks
ICLR 2019
A Spline Theory of Deep Learning
ICML 2018
Spline Filters For End-to-End Deep Learning
ICML 2018