fengliu90
Machine Learning Researcher, Assistant Professor @ The University of Melbourne
The University of MelbourneMelbourne, Australia
Pinned Repositories
CTCT
This repo contains source code and datasets used in code for Deep transfer learning enables lesion tracing of circulating tumor cells(CTC-Tracer), published in Nature Communications (2022).
BFUDA
Code release for "Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation" (IJCAI 2020)
Butterfly
This is the source code for Butterfly: One-step Approach towards Wildly Unsupervised Domain Adaptation (NeurIPS'19 Workshop).
CommonClasses_ImageNet_CIFAR100
The common classes between ImageNet and CIFAR(10 or 100).
DK-for-TST
This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
MetaTesting
This is the source code for Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data (NeurIPS2021).
Openset_Learning_AOSR
This is the source code for Learning Bounds for Open-set Learning (ICML2021).
SAMMD
This is the source code for Maximum Mean Discrepancy is Aware of Adversarial Attacks (ICML2021).
SFER_code
This is the code for paper "Unsupervised Heterogeneous Domain Adaptation via Shared Fuzzy Equivalence Relations" (IEEE-TFS 2018)
TOHAN
Source code for NeurIPS 2021 paper "TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation".
fengliu90's Repositories
fengliu90/DK-for-TST
This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
fengliu90/MetaTesting
This is the source code for Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data (NeurIPS2021).
fengliu90/SFER_code
This is the code for paper "Unsupervised Heterogeneous Domain Adaptation via Shared Fuzzy Equivalence Relations" (IEEE-TFS 2018)
fengliu90/Butterfly
This is the source code for Butterfly: One-step Approach towards Wildly Unsupervised Domain Adaptation (NeurIPS'19 Workshop).
fengliu90/BFUDA
Code release for "Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation" (IJCAI 2020)
fengliu90/CommonClasses_ImageNet_CIFAR100
The common classes between ImageNet and CIFAR(10 or 100).
fengliu90/Openset_Learning_AOSR
This is the source code for Learning Bounds for Open-set Learning (ICML2021).
fengliu90/SAMMD
This is the source code for Maximum Mean Discrepancy is Aware of Adversarial Attacks (ICML2021).
fengliu90/TOHAN
Source code for NeurIPS 2021 paper "TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation".
fengliu90/CSrankings
A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.
fengliu90/E-MixNet
This is the official code for the paper "How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?" (AAAI2021)
fengliu90/fengliu90.github.io
fengliu90/Friendly-Adversarial-Training
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger (ICML2020 Paper)
fengliu90/Geometry-aware-Instance-reweighted-Adversarial-Training
Based on the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
fengliu90/Open-set-domain-adaptation
Open set domain adaptation code DAOD (IEEE-TNNLS 2020)