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researcher

Shixiang Zhu

Georgia Institute of Technology

10 papers hereh-index 8278 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author3
  • last author3

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • stat.ML4
  • cs.LG3
  • cs.DS1
  • math.ST1
  • stat.AP1
affiliations
  • Georgia Institute of Technology
same name
  • Shixiang Zhu — 15 papers, h 12
  • Shixiang Zhu — 10 papers, h 3
  • Shixiang Zhu — 7 papers, h 3
  • Shixiang Zhu — 5 papers, h 2
  • Shixiang Zhu — 3 papers, h 1
  • Shixiang Zhu — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedLearning Temporal Point Processes via Reinforcement Learning

50 citations · 73 across the 10 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2023★ 4 cited

Counterfactual Generative Models for Time-Varying Treatments

Shenghao Wu, Wenbin Zhou, Minshuo Chen +1

Estimating the counterfactual outcome of treatment is essential for decision-making in public health and clinical science, among others. Often, treatments are administered in a seq…

stat.ML2023★ 1 cited

Conditional Generative Modeling for High-dimensional Marked Temporal Point Processes

Zheng Dong, Zekai Fan, Shixiang Zhu

Point processes offer a versatile framework for sequential event modeling. However, the computational challenges and constrained representational power of the existing point proces…

stat.ML2018★ 4 cited

Crime Event Embedding with Unsupervised Feature Selection

Shixiang Zhu, Yao Xie

We present a novel event embedding algorithm for crime data that can jointly capture time, location, and the complex free-text component of each event. The embedding is achieved by…

stat.ML2017

Crime incidents embedding using restricted Boltzmann machines

Shixiang Zhu, Yao Xie

We present a new approach for detecting related crime series, by unsupervised learning of the latent feature embeddings from narratives of crime record via the Gaussian-Bernoulli R…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.