dblp: Pranav Kulkarni (original) (raw)

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This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.

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2020 – today

• 2026
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  [i17]
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    Pranav Kulkarni, Leo Sünkel, Michael Kölle:
    An Adaptive Purification Controller for Quantum Networks: Dynamic Protocol Selection and Multipartite Distillation. CoRR abs/2601.18351 (2026)
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  [i16]
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    Pranav Kulkarni, Junfeng Guo, Heng Huang:
    X-Mark: Saliency-Guided Robust Dataset Ownership Verification for Medical Imaging. CoRR abs/2602.09284 (2026)
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  [i15]
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    Pranav Kulkarni, Brajesh K. Lal, Georges Jreij, Sai Vallamchetla, Langford Green, Jenifer Voeks, John Huston, Lloyd Edwards, George Howard, Bradley A. Maron, Thomas G. Brott, James F. Meschia, Florence X. Doo, Heng Huang:
    CRESTomics: Analyzing Carotid Plaques in the CREST-2 Trial with a New Additive Classification Model. CoRR abs/2603.04309 (2026)
• 2025
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  [j13]
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    Peter I. Kamel, Adway U. Kanhere, Pranav Kulkarni, Mazhar Khalid, Rachel Steger, Uttam Bodanapally, Dheeraj Gandhi, Vishwa S. Parekh, Paul H. Yi:
    Optimizing Acute Stroke Segmentation on MRI Using Deep Learning: Self-Configuring Neural Networks Provide High Performance Using Only DWI Sequences. J. Imaging Inform. Medicine 38(2): 717-726 (2025)
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  [j12]
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    Peter I. Kamel, Mazhar Khalid, Rachel Steger, Adway U. Kanhere, Pranav Kulkarni, Vishwa S. Parekh, Paul H. Yi, Dheeraj Gandhi, Uttam Bodanapally:
    Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts. J. Imaging Inform. Medicine 38(3): 1484-1495 (2025)
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  [j11]
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    Devina Chatterjee, Adway U. Kanhere, Florence X. Doo, Jerry Zhao, Andrew Chan, Alexander Welsh, Pranav Kulkarni, Annie Trang, Vishwa S. Parekh, Paul H. Yi:
    Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population. J. Imaging Inform. Medicine 38(3): 1628-1641 (2025)
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  [c25]
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    Pranav Kulkarni, Alan C. O'Connor, Frank M. Yaul:
    Graph Neural Network Guided Search for Power Grid Topology Correction. IEEECONF 2025: 1080-1086
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  [c24]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    On the Efficiency of a Toeplitz Covariance Matrix Construction Approach for DOA Estimation. IEEECONF 2025: 1719-1723
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  [c23]
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    Sravya Malladi, Pranav Kulkarni:
    Integrating Real-ESRGAN with CNN Models for UAV Image Based Plant Disease Detection. FedCSIS (Position Papers) 2025: 69-73
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  [c22]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Generalized Constructions of Weight-Constrained Sparse Arrays. ICASSP Workshops 2025: 1-5
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  [c21]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Interpolation for Weight-Constrained Nested Arrays Having Non-Central ULA Segments in the Coarray. ICASSP 2025: 1-5
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  [c20]
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    Jason Uwaeze, Pranav Kulkarni, Vladimir Braverman, Michael A. Jacobs, Vishwa S. Parekh:
    Generative Counterfactual Augmentation for Bias Mitigation. ICCVW 2025: 1164-1171
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  [i14]
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    Tianyi Xiong, Yi Ge, Ming Li, Zuolong Zhang, Pranav Kulkarni, Kaishen Wang, Qi He, Zeying Zhu, Chenxi Liu, Ruibo Chen, Tong Zheng, Yanshuo Chen, Xiyao Wang, Renrui Zhang, Wenhu Chen, Heng Huang:
    Multi-Crit: Benchmarking Multimodal Judges on Pluralistic Criteria-Following. CoRR abs/2511.21662 (2025)
• 2024
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  [j10]
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    Delvin Varghese, Hafeni Mthoko, Jessica L. Watterson, Pranav Kulkarni, Dan Richardson, Shaimaa Lazem, Patrick Olivier:
    Shadow Program Committee: Designing for Diversity and Equity within Academic Communities. ACM J. Comput. Sustain. Soc. 2(1): 2:1-2:24 (2024)
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  [j9]
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    Pranav Kulkarni, Adway U. Kanhere, Eliot L. Siegel, Paul H. Yi, Vishwa S. Parekh:
    ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging. J. Imaging Inform. Medicine 37(6): 3250-3263 (2024)
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  [j8]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Weight-Constrained Sparse Arrays For Direction of Arrival Estimation Under High Mutual Coupling. IEEE Trans. Signal Process. 72: 4444-4462 (2024)
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  [c19]
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    Pranav Kulkarni, Reuben Kirkham, Ling Wu, Roisin McNaney:
    Designing for Participatory Data Governance: Insights from People with Parkinson's. Conference on Designing Interactive Systems 2024
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  [c18]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Efficient Use of Non-Central ULA Segments in the Coarrays of Weight-Constrained Sparse Arrays. IEEECONF 2024: 79-83
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  [c17]
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    Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh:
    Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels. CVPR Workshops 2024: 2380-2387
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  [c16]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Sparse, Weight-Constrained Arrays With O(N) Aperture for Reduced Mutual Coupling. ICASSP 2024: 12891-12895
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  [c15]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Weight-Constrained Nested Arrays with w(1)=w(2)=0w(1) = w(2) = 0w(1)=w(2)=0 for Reduced Mutual Coupling. SAM 2024: 1-5
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  [c14]
  Pranav Kulkarni, Andrew Chan, Nithya Navarathna, Skylar Chan, Paul H. Yi, Vishwa Sanjay Parekh:
  Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations. MIDL 2024: 793-821
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  [c13]
  Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
  From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray Classification. ML4H@NeurIPS 2024: 623-635
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  [c12]
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    Skylar Chan, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh:
    Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification. QCE 2024: 572-582
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  [i13]
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    Pranav Kulkarni, Andrew Chan, Nithya Navarathna, Skylar Chan, Paul H. Yi, Vishwa S. Parekh:
    Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations. CoRR abs/2402.05713 (2024)
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  [i12]
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    Pranav Kulkarni, Adway U. Kanhere, Dharmam Savani, Andrew Chan, Devina Chatterjee, Paul H. Yi, Vishwa S. Parekh:
    Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations. CoRR abs/2403.15218 (2024)
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  [i11]
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    Pranav Kulkarni, Adway U. Kanhere, Harshita Kukreja, Vivian Zhang, Paul H. Yi, Vishwa S. Parekh:
    Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning. CoRR abs/2404.07374 (2024)
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  [i10]
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    Skylar Chan, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh:
    Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification. CoRR abs/2405.00156 (2024)
• 2023
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  [j7]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Periodicity-Aware Signal Denoising Using Capon-Optimized Ramanujan Filter Banks and Pruned Ramanujan Dictionaries. IEEE Trans. Signal Process. 71: 494-511 (2023)
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  [c11]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    On the Efficiency of Coarray-Based Direction of Arrival Estimation. ACSSC 2023: 1334-1338
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  [c10]
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    Farheen Siddiqui, Delvin Varghese, Pushpendra Singh, Sunita Bapuji Bayyavarapu, Stephen Lindsay, Dharshani Chandrasekara, Pranav Kulkarni, Ling Wu, Taghreed Alshehri, Patrick Olivier:
    Exploring the digital support needs of caregivers of people with serious mental illness. CHI 2023: 560:1-560:16
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  [c9]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Interpolation Filter Model For Ramanujan Subspace Signals. ICASSP 2023: 1-5
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  [c8]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Difference Coarrays of Rational Arrays. ICASSP 2023: 1-5
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  [i9]
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    Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
    Surgical Aggregation: A Federated Learning Framework for Harmonizing Distributed Datasets with Diverse Tasks. CoRR abs/2301.06683 (2023)
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  [i8]
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    Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh:
    SegViz: A Federated Learning Framework for Medical Image Segmentation from Distributed Datasets with Different and Incomplete Annotations. CoRR abs/2301.07074 (2023)
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  [i7]
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    Pranav Kulkarni, Ziqing Ji, Yan Xu, Marko Neskovic, Kevin Nolan:
    Exploring Semantic Perturbations on Grover. CoRR abs/2302.00509 (2023)
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  [i6]
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    Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
    Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels. CoRR abs/2303.06180 (2023)
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  [i5]
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    Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
    Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery. CoRR abs/2305.07637 (2023)
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  [i4]
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    Pranav Kulkarni, Sean Garin, Adway U. Kanhere, Eliot L. Siegel, Paul H. Yi, Vishwa S. Parekh:
    High-Throughput AI Inference for Medical Image Classification and Segmentation using Intelligent Streaming. CoRR abs/2305.15617 (2023)
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  [i3]
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    Pranav Kulkarni, Adway U. Kanhere, Eliot L. Siegel, Paul H. Yi, Vishwa S. Parekh:
    One Copy Is All You Need: Resource-Efficient Streaming of Medical Imaging Data at Scale. CoRR abs/2307.00438 (2023)
• 2022
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  [j6]
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    Pranav Kulkarni, Reuben Kirkham, Roisin McNaney:
    Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. Sensors 22(10): 3893 (2022)
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  [j5]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Non-Integer Arrays for Array Signal Processing. IEEE Trans. Signal Process. 70: 5457-5472 (2022)
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  [c7]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Rational Arrays for DOA Estimation: New Insights and Performance Evaluation. IEEECONF 2022: 91-95
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  [c6]
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    Roisin McNaney, Catherine Morgan, Pranav Kulkarni, Julio Vega, Farnoosh Heidarivincheh, Ryan McConville, Alan L. Whone, Mickey Kim, Reuben Kirkham, Ian Craddock:
    Exploring Perceptions of Cross-Sectoral Data Sharing with People with Parkinson's. CHI 2022: 280:1-280:14
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  [c5]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Rational Arrays for DOA Estimation. ICASSP 2022: 5008-5012
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  [i2]
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    Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
    From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning. CoRR abs/2211.06212 (2022)
• 2021
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  [c4]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Feature Engineering for DOA Estimation using a Convolutional Neural Network, for Sparse Arrays. ACSCC 2021: 246-250
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  [c3]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    Periodic Signal Denoising: An Analysis-Synthesis Framework Based on Ramanujan Filter Banks and Dictionaries. ICASSP 2021: 5100-5104
• 2020
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  [j4]
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    Peeyush Sahay, Izaz Ahamed Shaik Rasheed, Pranav Kulkarni, Shubham Anand Jain, Ameya Anjarlekar, P. Radhakrishna, Vikram M. Gadre:
    Generalized Fractional Ambiguity Function and Its Applications. Circuits Syst. Signal Process. 39(10): 4980-5019 (2020)
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  [j3]
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    Peeyush Sahay, B. S. Teza, Pranav Kulkarni, P. Radhakrishna, Vikram M. Gadre:
    Adaptive Generalised Fractional Spectrogram and Its Applications. Circuits Syst. Signal Process. 39(12): 5982-6033 (2020)
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  [j2]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    On the Zeros of Ramanujan Filters. IEEE Signal Process. Lett. 27: 735-739 (2020)
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  [c2]
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    Pranav Kulkarni, P. P. Vaidyanathan:
    K-SVD based Periodicity Dictionary Learning. ACSSC 2020: 1333-1337

2010 – 2019

• 2019
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  [c1]
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    Yao Zhu, Saksham Suri, Pranav Kulkarni, Yueru Chen, Jiali Duan, C.-C. Jay Kuo:
    An Interpretable Generative Model for Handwritten Digits Synthesis. ICIP 2019: 1910-1914
• 2018
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  [j1]
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    Rasmus Krempel, Pranav Kulkarni, Annie Yim, Ulrich Lang, Bianca Habermann, Peter Frommolt:
    Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB). BMC Bioinform. 19(1): 156:1-156:10 (2018)
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  [i1]
  Yao Zhu, Saksham Suri, Pranav Kulkarni, Yueru Chen, Jiali Duan, C.-C. Jay Kuo:
  An Interpretable Generative Model for Handwritten Digit Image Synthesis. CoRR abs/1811.04507 (2018)

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