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Found 13 papers, 6 papers with code
A high-accuracy multi-model mixing retrosynthetic method
The field of computer-aided synthesis planning (CASP) has seen rapid advancements in recent years, achieving significant progress across various algorithmic benchmarks.
A WT-ResNet based fault diagnosis model for the urban rail train transmission system
This study presents a novel fault diagnosis model for urban rail transit systems based on Wavelet Transform Residual Neural Network (WT-ResNet).
MMPolymer: A Multimodal Multitask Pretraining Framework for Polymer Property Prediction
Experiments show that MMPolymer achieves state-of-the-art performance in downstream property prediction tasks.
Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity
Zeroth-order optimization (ZO) is a memory-efficient strategy for fine-tuning Large Language Models using only forward passes.
Ranking with Slot Constraints
We introduce the problem of ranking with slot constraints, which can be used to model a wide range of application problems -- from college admission with limited slots for different majors, to composing a stratified cohort of eligible participants in a medical trial.
Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step Retrosynthesis
Single-step retrosynthesis (SSR) in organic chemistry is increasingly benefiting from deep learning (DL) techniques in computer-aided synthesis design.
Ranked #1 on
Single-step retrosynthesis
on USPTO-50k
Assessing the efficacy of large language models in generating accurate teacher responses
(Tack et al., 2023) organized the shared task hosted by the 18th Workshop on Innovative Use of NLP for Building Educational Applications on generation of teacher language in educational dialogues.
Coordinating Distributed Example Orders for Provably Accelerated Training
Recent research on online Gradient Balancing (GraB) has revealed that there exist permutation-based example orderings for SGD that are guaranteed to outperform random reshuffling (RR).
Photo Rater: Photographs Auto-Selector with Deep Learning
Photo Rater is a computer vision project that uses neural networks to help photographers select the best photo among those that are taken based on the same scene.
MCTensor: A High-Precision Deep Learning Library with Multi-Component Floating-Point
In this paper, we introduce MCTensor, a library based on PyTorch for providing general-purpose and high-precision arithmetic for DL training.
Cyclical Kernel Adaptive Metropolis
We propose cKAM, cyclical Kernel Adaptive Metropolis, which incorporates a cyclical stepsize scheme to allow control for exploration and sampling.
GraB: Finding Provably Better Data Permutations than Random Reshuffling
To reduce the memory overhead, we leverage discrepancy minimization theory to propose an online Gradient Balancing algorithm (GraB) that enjoys the same rate as herding, while reducing the memory usage from $O(nd)$ to just $O(d)$ and computation from $O(n^2)$ to $O(n)$, where $d$ denotes the model dimension.
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm
With the transition from people's traditional `brick-and-mortar' shopping to online mobile shopping patterns in web 2. 0 $\mathit{era}$, the recommender system plays a critical role in E-Commerce and E-Retails.
