David Jacobs
19 papers · 2017–2024 · 7 conferences · across top CS/AI conferences
Achievements
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🐝 Cross-Pollinator (12) 🏃 Academic Marathon (7) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🌈 Renaissance Researcher (6)
🌍
Conference Polyglot
(7)
🏃
Academic Marathon
(7)
🌈
Renaissance Researcher
(6)
👑
Triple Crown
🧬
Topic Evolution
⚡
Prolific Year
(5)
💎
Century Club
(19)
🚀
Conference Pioneer
🗃️
Keyword Collector
(87)
🔥
Unstoppable
(8)
Conferences
NIPS (8)
CVPR (3)
ICCV (3)
ICLR (2)
AISTATS (1)
ECCV (1)
ICML (1)
Top co-authors
Research topics
Keywords
contrastive learning
(3)
neural tangent kernel
(3)
representation learning
(3)
convolutional neural network
(2)
eigenvalue decay
(2)
unsupervised learning
(2)
adversarial training
(2)
zero-shot learning
(1)
non-convex optimization
(1)
stochastic gradient descent
(1)
model security
(1)
data poisoning
(1)
domain generalization
(1)
domain adaptation
(1)
in-context learning
(1)
few-shot learning
(1)
self-supervised learning
(1)
video captioning
(1)
video generation
(1)
scene understanding
(1)
Papers
CALVIN: Improved Contextual Video Captioning via Instruction Tuning
NIPS 2024
LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation
ICCV 2023
Hyperbolic Contrastive Learning for Visual Representations Beyond Objects
CVPR 2023
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach
NIPS 2023
Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models
ICCV 2023
HaLP: Hallucinating Latent Positives for Skeleton-Based Self-Supervised Learning of Actions
CVPR 2023
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
NIPS 2022
Autoregressive Perturbations for Data Poisoning
NIPS 2022
Shift Invariance Can Reduce Adversarial Robustness
NIPS 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training
ICCV 2021
Robust Contrastive Learning Using Negative Samples with Diminished Semantics
NIPS 2021
Frequency Bias in Neural Networks for Input of Non-Uniform Density
ICML 2020
On the Similarity between the Laplace and Neural Tangent Kernels
NIPS 2020
SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation
CVPR 2020
Adversarially robust transfer learning
ICLR 2020
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
NIPS 2019
Stabilizing Adversarial Nets with Prediction Methods
ICLR 2018
Automated Inference with Adaptive Batches
AISTATS 2017