activity
20182026
most citedStochastic Hyperparameter Optimization through Hypernetworks

80 citations · 197 across the 25 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.LG2024★ 3 cited

LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models

Zhengyi Wang, Jonathan Lorraine, Yikai Wang +4

This work explores expanding the capabilities of large language models (LLMs) pretrained on text to generate 3D meshes within a unified model. This offers key advantages of (1) lev…

cs.LG2024

Multi-student Diffusion Distillation for Better One-step Generators

Yanke Song, Jonathan Lorraine, Weili Nie +2

Diffusion models achieve high-quality sample generation at the cost of a lengthy multistep inference procedure. To overcome this, diffusion distillation techniques produce student…

cs.LG2024★ 1 cited

JacNet: Learning Functions with Structured Jacobians

Jonathan Lorraine, Safwan Hossain

Neural networks are trained to learn an approximate mapping from an input domain to a target domain. Incorporating prior knowledge about true mappings is critical to learning a use…

cs.LG2024

Scalable Nested Optimization for Deep Learning

Jonathan Lorraine

Gradient-based optimization has been critical to the success of machine learning, updating a single set of parameters to minimize a single loss. A growing number of applications re…

cs.LG2024

Improving Hyperparameter Optimization with Checkpointed Model Weights

Nikhil Mehta, Jonathan Lorraine, Steve Masson +4

When training deep learning models, the performance depends largely on the selected hyperparameters. However, hyperparameter optimization (HPO) is often one of the most expensive p…

cs.LG2024★ 1 cited

Training Data Attribution via Approximate Unrolled Differentiation

Juhan Bae, Wu Lin, Jonathan Lorraine +1

Many training data attribution (TDA) methods aim to estimate how a model's behavior would change if one or more data points were removed from the training set. Methods based on imp…

cs.CV2024

LATTE3D: Large-scale Amortized Text-To-Enhanced3D Synthesis

Kevin Xie, Jonathan Lorraine, Tianshi Cao +5

Recent text-to-3D generation approaches produce impressive 3D results but require time-consuming optimization that can take up to an hour per prompt. Amortized methods like ATT3D o…