David Jacobs
19 papers · 2017–2024 · 7 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (43) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Pioneer
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Triple Crown
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Topic Evolution
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Conference Pioneer
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
ποΈ
Keyword Collector
(94)
Top co-authors
Research topics
Machine Learning
(15)
Deep Learning
(11)
Learning Types Β· Machine Learning
(8)
Optimization & Theory
(7)
Computer Vision
(6)
Learning Types Β· Deep Learning
(5)
Artificial Intelligence
(4)
Core AI
(4)
Models
(4)
Analysis
(3)
Application Areas
(3)
Architectures
(3)
Core Methods
(3)
Techniques
(3)
Generation
(2)
Keywords
representation learning
(3)
neural tangent kernel
(3)
contrastive learning
(3)
stochastic gradient descent
(2)
adversarial training
(2)
unsupervised learning
(2)
eigenvalue decay
(2)
domain adaptation
(2)
adversarial robustness
(2)
few-shot learning
(2)
convolutional neural network
(2)
domain generalization
(1)
data poisoning
(1)
transfer learning
(1)
non-convex optimization
(1)
zero-shot learning
(1)
self-supervised learning
(1)
model security
(1)
video captioning
(1)
video generation
(1)
Papers
CALVIN: Improved Contextual Video Captioning via Instruction Tuning
NeurIPS 2024
HaLP: Hallucinating Latent Positives for Skeleton-Based Self-Supervised Learning of Actions
CVPR 2023
Hyperbolic Contrastive Learning for Visual Representations Beyond Objects
CVPR 2023
LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation
ICCV 2023
Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models
ICCV 2023
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach
NeurIPS 2023
Autoregressive Perturbations for Data Poisoning
NeurIPS 2022
Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer
ECCV 2022
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels
NeurIPS 2022
Low Curvature Activations Reduce Overfitting in Adversarial Training
ICCV 2021
Robust Contrastive Learning Using Negative Samples with Diminished Semantics
NeurIPS 2021
Shift Invariance Can Reduce Adversarial Robustness
NeurIPS 2021
Adversarially robust transfer learning
ICLR 2020
Frequency Bias in Neural Networks for Input of Non-Uniform Density
ICML 2020
On the Similarity between the Laplace and Neural Tangent Kernels
NeurIPS 2020
SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation
CVPR 2020
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
NeurIPS 2019
Stabilizing Adversarial Nets with Prediction Methods
ICLR 2018
Automated Inference with Adaptive Batches
AISTATS 2017