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2020 – today
- 2024
[j75]Mustafa Munir
, Saloni Modi, Geffen Cooper, Huntae Kim, Radu Marculescu:
Three Decades of Low Power: From Watts to Wisdom. IEEE Access 12: 19447-19458 (2024)- [j74]Guihong Li, Duc Hoang, Kartikeya Bhardwaj, Ming Lin, Zhangyang Wang, Radu Marculescu:
Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 7618-7635 (2024) - [c170]Guihong Li, Hsiang Hsu, Chun-Fu Richard Chen, Radu Marculescu:
Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models. CVPR Workshops 2024: 227-234 - [c169]Md Mostafijur Rahman, Mustafa Munir, Debesh Jha, Ulas Bagci, Radu Marculescu:
PP-SAM: Perturbed Prompts for Robust Adaption of Segment Anything Model for Polyp Segmentation. CVPR Workshops 2024: 4989-4995 - [c168]William Avery, Mustafa Munir, Radu Marculescu:
Scaling Graph Convolutions for Mobile Vision. CVPR Workshops 2024: 5857-5865 - [c167]Mustafa Munir, William Avery, Md Mostafijur Rahman, Radu Marculescu:
GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs. CVPR 2024: 6118-6127 - [c166]Yuedong Yang, Hung-Yueh Chiang, Guihong Li, Diana Marculescu, Radu Marculescu:
Cache and Reuse: Rethinking the Efficiency of On-device Transfer Learning. CVPR Workshops 2024: 8040-8049 - [c165]Md Mostafijur Rahman, Mustafa Munir, Radu Marculescu:
EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation. CVPR 2024: 11769-11779 - [c164]Guihong Li, Hsiang Hsu, Chun-Fu Chen, Radu Marculescu:
Machine Unlearning for Image-to-Image Generative Models. ICLR 2024 - [c163]Geffen Cooper, Radu Marculescu:
Beyond Thresholds: A General Approach to Sensor Selection for Practical Deep Learning-based HAR. IoTDI 2024: 1-12 - [c162]Allen-Jasmin Farcas, Myungjin Lee, Ali Payani, Hugo Latapie, Ramana Rao Kompella, Radu Marculescu:
CHESSFL: Clustering Hierarchical Embeddings for Semi-Supervised Federated Learning. IoTDI 2024: 122-133 - [c161]Allen-Jasmin Farcas, Geffen Cooper, Hyun Joon Song, Afnan Mir, Vincent Liew, Chloe Tang, Prithvi Senthilkumar, Tiani Chen-Troester, Radu Marculescu:
Demo Abstract: Online Training and Inference for On-Device Monocular Depth Estimation. IoTDI 2024: 221-222 - [c160]Geffen Cooper, Tianda Huang, Radu Marculescu:
Demo Abstract: A Prototype for Machine Learning with Batteryless Sensors. IoTDI 2024: 223-224 - [c159]Md Mostafijur Rahman, Radu Marculescu:
G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation. WACV 2024: 7713-7722 - [i43]Guihong Li, Hsiang Hsu, Chun-Fu Chen, Radu Marculescu:
Machine Unlearning for Image-to-Image Generative Models. CoRR abs/2402.00351 (2024) - [i42]Arash Amini, Yigit Ege Bayiz, Ashwin Ram, Radu Marculescu, Ufuk Topcu:
News Source Credibility Assessment: A Reddit Case Study. CoRR abs/2402.10938 (2024) - [i41]Yigit Ege Bayiz, Arash Amini, Radu Marculescu, Ufuk Topcu:
Susceptibility of Communities against Low-Credibility Content in Social News Websites. CoRR abs/2403.10705 (2024) - [i40]Mustafa Munir, William Avery, Md Mostafijur Rahman, Radu Marculescu:
GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs. CoRR abs/2405.06849 (2024) - [i39]Md Mostafijur Rahman, Mustafa Munir, Radu Marculescu:
EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation. CoRR abs/2405.06880 (2024) - [i38]Md Mostafijur Rahman, Mustafa Munir, Debesh Jha, Ulas Bagci, Radu Marculescu:
PP-SAM: Perturbed Prompts for Robust Adaptation of Segment Anything Model for Polyp Segmentation. CoRR abs/2405.16740 (2024) - [i37]Tanvir Mahmud, Mustafa Munir, Radu Marculescu, Diana Marculescu:
Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior. CoRR abs/2406.04873 (2024) - [i36]William Avery, Mustafa Munir, Radu Marculescu:
Scaling Graph Convolutions for Mobile Vision. CoRR abs/2406.05850 (2024) - [i35]Hiroki Matsutani, Radu Marculescu:
A Tiny Supervised ODL Core with Auto Data Pruning for Human Activity Recognition. CoRR abs/2408.01283 (2024) - [i34]Ashwin Ram, Yigit Ege Bayiz, Arash Amini, Mustafa Munir, Radu Marculescu:
CrediRAG: Network-Augmented Credibility-Based Retrieval for Misinformation Detection in Reddit. CoRR abs/2410.12061 (2024) - [i33]Hiroki Matsutani, Masaaki Kondo, Kazuki Sunaga, Radu Marculescu:
Skip2-LoRA: A Lightweight On-device DNN Fine-tuning Method for Low-cost Edge Devices. CoRR abs/2410.21073 (2024) - 2023
- [j73]Oscar Torres Sanchez, Duarte M. G. Raposo, André Rodrigues, Fernando Boavida, Radu Marculescu, Kongyang Chen, Jorge Sá Silva:
An IIoT-Based Approach to the Integrated Management of Machinery in the Construction Industry. IEEE Access 11: 6331-6350 (2023) - [j72]Allen-Jasmin Farcas, Radu Marculescu:
Teaching Edge AI at the Undergraduate Level: A Hardware-Software Co-Design Approach. Computer 56(11): 30-38 (2023) - [j71]Zihui Xue, Yuedong Yang, Radu Marculescu:
SUGAR: Efficient Subgraph-Level Training via Resource-Aware Graph Partitioning. IEEE Trans. Computers 72(11): 3167-3177 (2023) - [j70]Ümit Y. Ogras, Radu Marculescu, Trevor N. Mudge, Michael Kishinevsky:
Introduction to the Special Issue on Domain-Specific System-on-Chip Architectures and Run-Time Management Techniques. ACM Trans. Embed. Comput. Syst. 22(2): 27:1-27:3 (2023) - [j69]Anish Krishnakumar, Ümit Y. Ogras, Radu Marculescu, Michael Kishinevsky, Trevor N. Mudge:
Domain-Specific Architectures: Research Problems and Promising Approaches. ACM Trans. Embed. Comput. Syst. 22(2): 28:1-28:26 (2023) - [j68]A. Alper Goksoy, Guihong Li, Sumit K. Mandal, Ümit Y. Ogras, Radu Marculescu:
CANNON: Communication-Aware Sparse Neural Network Optimization. IEEE Trans. Emerg. Top. Comput. 11(4): 882-894 (2023) - [c158]Sofia Hurtado, Radu Marculescu:
Quarantine in Motion: A Graph Learning and Multi-Agent Reinforcement Learning Framework to Reduce Disease Transmission Without Lockdown. ASONAM 2023: 82-89 - [c157]Mustafa Munir, William Avery, Radu Marculescu:
MobileViG: Graph-Based Sparse Attention for Mobile Vision Applications. CVPR Workshops 2023: 2211-2219 - [c156]Zihui Xue, Radu Marculescu:
Dynamic Multimodal Fusion. CVPR Workshops 2023: 2575-2584 - [c155]Yuedong Yang, Guihong Li, Radu Marculescu:
Efficient On-Device Training via Gradient Filtering. CVPR 2023: 3811-3820 - [c154]Duc N. M. Hoang, Shiwei Liu, Radu Marculescu, Zhangyang Wang:
Revisiting Pruning at Initialization Through the Lens of Ramanujan Graph. ICLR 2023 - [c153]Guihong Li, Yuedong Yang, Kartikeya Bhardwaj, Radu Marculescu:
ZiCo: Zero-shot NAS via inverse Coefficient of Variation on Gradients. ICLR 2023 - [c152]Guihong Li, Kartikeya Bhardwaj, Yuedong Yang, Radu Marculescu:
TIPS: Topologically Important Path Sampling for Anytime Neural Networks. ICML 2023: 19343-19359 - [c151]Allen-Jasmin Farcas, Myungjin Lee, Ramana Rao Kompella, Hugo Latapie, Gustavo de Veciana, Radu Marculescu:
MOHAWK: Mobility and Heterogeneity-Aware Dynamic Community Selection for Hierarchical Federated Learning. IoTDI 2023: 249-261 - [c150]Jorge Eduardo Rivadeneira, María B. Jiménez, Radu Marculescu, André Rodrigues, Fernando Boavida, Jorge Sá Silva:
A Blockchain-Based Privacy-Preserving Model for Consent and Transparency in Human-Centered Internet of Things. IoTDI 2023: 301-314 - [c149]Allen-Jasmin Farcas, Radu Marculescu:
Demo Abstract: A Hardware Prototype Targeting Federated Learning with User Mobility and Device Heterogeneity. IoTDI 2023: 486-487 - [c148]Md Mostafijur Rahman, Radu Marculescu:
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation. MIDL 2023: 1526-1544 - [c147]Yuedong Yang, Hung-Yueh Chiang, Guihong Li, Diana Marculescu, Radu Marculescu:
Efficient Low-rank Backpropagation for Vision Transformer Adaptation. NeurIPS 2023 - [c146]Md Mostafijur Rahman, Radu Marculescu:
Medical Image Segmentation via Cascaded Attention Decoding. WACV 2023: 6211-6220 - [i32]Yuedong Yang, Guihong Li, Radu Marculescu:
Efficient On-device Training via Gradient Filtering. CoRR abs/2301.00330 (2023) - [i31]Guihong Li, Yuedong Yang, Kartikeya Bhardwaj, Radu Marculescu:
ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients. CoRR abs/2301.11300 (2023) - [i30]Md Mostafijur Rahman, Radu Marculescu:
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation. CoRR abs/2303.16892 (2023) - [i29]Guihong Li, Kartikeya Bhardwaj, Yuedong Yang, Radu Marculescu:
TIPS: Topologically Important Path Sampling for Anytime Neural Networks. CoRR abs/2305.08021 (2023) - [i28]Mustafa Munir, William Avery, Radu Marculescu:
MobileViG: Graph-Based Sparse Attention for Mobile Vision Applications. CoRR abs/2307.00395 (2023) - [i27]Guihong Li, Duc Hoang, Kartikeya Bhardwaj, Ming Lin, Zhangyang Wang, Radu Marculescu:
Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities. CoRR abs/2307.01998 (2023) - [i26]Yuedong Yang, Hung-Yueh Chiang, Guihong Li, Diana Marculescu, Radu Marculescu:
Efficient Low-rank Backpropagation for Vision Transformer Adaptation. CoRR abs/2309.15275 (2023) - [i25]Md Mostafijur Rahman, Radu Marculescu:
G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation. CoRR abs/2310.16175 (2023) - [i24]Guihong Li, Hsiang Hsu, Chun-Fu Chen, Radu Marculescu:
Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models. CoRR abs/2312.14923 (2023) - 2022
- [j67]A. Alper Goksoy, Anish Krishnakumar, Md Sahil Hassan, Allen-Jasmin Farcas, Ali Akoglu, Radu Marculescu, Ümit Y. Ogras:
DAS: Dynamic Adaptive Scheduling for Energy-Efficient Heterogeneous SoCs. IEEE Embed. Syst. Lett. 14(1): 51-54 (2022) - [c145]Sofia Hurtado, Radu Marculescu, Justin A. Drake:
Quarantine in Motion: A Graph Learning Framework to Reduce Disease Transmission Without Lockdown. ASONAM 2022: 454-461 - [c144]Allen-Jasmin Farcas, Xiaohan Chen, Zhangyang Wang, Radu Marculescu:
Model elasticity for hardware heterogeneity in federated learning systems. FedEdge@MobiCom 2022: 19-24 - [c143]Anish Krishnakumar, Radu Marculescu, Ümit Y. Ogras:
INDENT: Incremental Online Decision Tree Training for Domain-Specific Systems-on-Chip. ICCAD 2022: 164:1-164:9 - [c142]Daniel W. Bliss, Tutu Ajayi, Ali Akoglu, Ilkin Aliyev, Toygun Basaklar, Leul Belayneh, David T. Blaauw, John S. Brunhaver, Chaitali Chakrabarti, Liangliang Chang, Kuan-Yu Chen, Ming-Hung Chen, Xing Chen, Alex R. Chiriyath, Alhad Daftardar, Ronald G. Dreslinski, Arindam Dutta, Allen-Jasmin Farcas, Y. Fu, A. Alper Goksoy, X. He, Md Sahil Hassan, Andrew Herschfelt, Jacob Holtom, Hun-Seok Kim, A. N. Krishnakumar, Yang Li, Owen Ma, Joshua Mack, Saurav Mallik, Sumit K. Mandal, Radu Marculescu, Brittany M. McCall, Trevor N. Mudge, Ümit Y. Ogras, Vishrut Pandey, Saquib Ahmad Siddiqui, Yu-Hsiu Sun, Adarsh A. Venkataramani, Xiangdong Wei, B. R. Willis, Hanguang Yu, Yufan Yue:
Enabling Software-Defined RF Convergence with a Novel Coarse-Scale Heterogeneous Processor. ISCAS 2022: 443-447 - [c141]Dawei Liang, Guihong Li, Rebecca Adaimi, Radu Marculescu, Edison Thomaz:
AudioIMU: Enhancing Inertial Sensing-Based Activity Recognition with Acoustic Models. ISWC 2022: 44-48 - [i23]Zihui Xue, Yuedong Yang, Mengtian Yang, Radu Marculescu:
SUGAR: Efficient Subgraph-level Training via Resource-aware Graph Partitioning. CoRR abs/2202.00075 (2022) - [i22]Zihui Xue, Radu Marculescu:
Dynamic Multimodal Fusion. CoRR abs/2204.00102 (2022) - 2021
- [j66]Kartikeya Bhardwaj, Naveen Suda, Radu Marculescu:
EdgeAl: A Vision for Deep Learning in the IoT Era. IEEE Des. Test 38(4): 37-43 (2021) - [j65]Guihong Li, Sumit K. Mandal, Ümit Y. Ogras, Radu Marculescu:
FLASH: Fast Neural Architecture Search with Hardware Optimization. ACM Trans. Embed. Comput. Syst. 20(5s): 63:1-63:26 (2021) - [c140]Sofia Hurtado, Radu Marculescu, Justin A. Drake, Ravi Srinivasan:
Pruning digital contact networks for meso-scale epidemic surveillance using foursquare data. ASONAM 2021: 423-430 - [c139]Yuedong Yang, Zihui Xue, Radu Marculescu:
Anytime Depth Estimation with Limited Sensing and Computation Capabilities on Mobile Devices. CoRL 2021: 609-618 - [c138]Kartikeya Bhardwaj, Guihong Li, Radu Marculescu:
How Does Topology Influence Gradient Propagation and Model Performance of Deep Networks With DenseNet-Type Skip Connections? CVPR 2021: 13498-13507 - [i21]Guihong Li, Sumit K. Mandal, Ümit Y. Ogras, Radu Marculescu:
FLASH: Fast Neural Architecture Search with Hardware Optimization. CoRR abs/2108.00568 (2021) - [i20]A. Alper Goksoy, Anish Krishnakumar, Md Sahil Hassan, Allen-Jasmin Farcas, Ali Akoglu, Radu Marculescu, Ümit Y. Ogras:
DAS: Dynamic Adaptive Scheduling for Energy-Efficient Heterogeneous SoCs. CoRR abs/2109.11069 (2021) - 2020
- [j64]Anderson L. Sartor, Anish Krishnakumar, Samet E. Arda, Ümit Y. Ogras, Radu Marculescu:
HiLITE: Hierarchical and Lightweight Imitation Learning for Power Management of Embedded SoCs. IEEE Comput. Archit. Lett. 19(1): 63-67 (2020) - [j63]Samet E. Arda, Anish Krishnakumar, A. Alper Goksoy, Nirmal Kumbhare, Joshua Mack, Anderson L. Sartor, Ali Akoglu, Radu Marculescu, Ümit Y. Ogras:
DS3: A System-Level Domain-Specific System-on-Chip Simulation Framework. IEEE Trans. Computers 69(8): 1248-1262 (2020) - [j62]Anish Krishnakumar, Samet E. Arda, A. Alper Goksoy, Sumit K. Mandal, Ümit Y. Ogras, Anderson L. Sartor, Radu Marculescu:
Runtime Task Scheduling Using Imitation Learning for Heterogeneous Many-Core Systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(11): 4064-4077 (2020) - [c137]Allen-Jasmin Farcas, Guihong Li, Kartikeya Bhardwaj, Radu Marculescu:
A Hardware Prototype Targeting Distributed Deep Learning for On-device Inference. CVPR Workshops 2020: 1600-1601 - [c136]Kartikeya Bhardwaj, Wei Chen, Radu Marculescu:
INVITED: New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design. DAC 2020: 1-6 - [c135]Brian Davis, Umang Bhatt, Kartikeya Bhardwaj, Radu Marculescu, José M. F. Moura:
On Network Science and Mutual Information for Explaining Deep Neural Networks. ICASSP 2020: 8399-8403 - [c134]Radu Marculescu, Diana Marculescu, Ümit Y. Ogras:
Edge AI: Systems Design and ML for IoT Data Analytics. KDD 2020: 3565-3566 - [c133]Chingyi Lin, Radu Marculescu:
Model Personalization for Human Activity Recognition. PerCom Workshops 2020: 1-7 - [c132]Wei Chen, Kartikeya Bhardwaj, Radu Marculescu:
FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning. ECML/PKDD (2) 2020: 348-363 - [i19]Samet E. Arda, Anish Krishnakumar, A. Alper Goksoy, Nirmal Kumbhare, Joshua Mack, Anderson L. Sartor, Ali Akoglu, Radu Marculescu, Ümit Y. Ogras:
DS3: A System-Level Domain-Specific System-on-Chip Simulation Framework. CoRR abs/2003.09016 (2020) - [i18]Wei Chen, Kartikeya Bhardwaj, Radu Marculescu:
FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning. CoRR abs/2004.03657 (2020) - [i17]Alexandru Topirceanu, Mihai Udrescu, Radu Marculescu:
Centralized and decentralized isolation strategies and their impact on the COVID-19 pandemic dynamics. CoRR abs/2004.04222 (2020) - [i16]Anish Krishnakumar, Samet E. Arda, A. Alper Goksoy, Sumit K. Mandal, Ümit Y. Ogras, Anderson L. Sartor, Radu Marculescu:
Runtime Task Scheduling using Imitation Learning for Heterogeneous Many-Core Systems. CoRR abs/2007.09361 (2020) - [i15]Kartikeya Bhardwaj, Wei Chen, Radu Marculescu:
New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design. CoRR abs/2008.10805 (2020)
2010 – 2019
- 2019
- [j61]Chieh Lo, Radu Marculescu:
MetaNN: accurate classification of host phenotypes from metagenomic data using neural networks. BMC Bioinform. 20-S(12): 314:1-314:14 (2019) - [j60]Biresh Kumar Joardar, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Learning-Based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems. IEEE Trans. Computers 68(6): 852-866 (2019) - [j59]Kartikeya Bhardwaj, Chingyi Lin, Anderson L. Sartor, Radu Marculescu:
Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT. ACM Trans. Embed. Comput. Syst. 18(5s): 82:1-82:22 (2019) - [c131]Samet E. Arda, Anish Krishnakumar, A. Alper Goksoy, Joshua Mack, Nirmal Kumbhare, Anderson L. Sartor, Ali Akoglu, Radu Marculescu, Ümit Y. Ogras:
A simulation framework for domain-specific system-on-chips: work-in-progress. CODES+ISSS 2019: 3:1-3:2 - [c130]Sofia Hurtado, Poushali Ray, Radu Marculescu:
Bot Detection in Reddit Political Discussion. SocialSens@CPSIoTWeek 2019: 30-35 - [c129]Anderson Luiz Sartor, Pedro Henrique Exenberger Becker, Stephan Wong, Radu Marculescu, Antonio Carlos Schneider Beck:
Machine Learning-Based Processor Adaptability Targeting Energy, Performance, and Reliability. ISVLSI 2019: 158-163 - [i14]Brian Davis, Umang Bhatt, Kartikeya Bhardwaj, Radu Marculescu, José M. F. Moura:
NIF: A Framework for Quantifying Neural Information Flow in Deep Networks. CoRR abs/1901.08557 (2019) - [i13]Kartikeya Bhardwaj, Naveen Suda, Radu Marculescu:
Dream Distillation: A Data-Independent Model Compression Framework. CoRR abs/1905.07072 (2019) - [i12]Kartikeya Bhardwaj, Chingyi Lin, Anderson L. Sartor, Radu Marculescu:
Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT. CoRR abs/1907.11804 (2019) - [i11]Samet E. Arda, Anish Krishnakumar, A. Alper Goksoy, Joshua Mack, Nirmal Kumbhare, Anderson L. Sartor, Ali Akoglu, Radu Marculescu, Ümit Y. Ogras:
Work-in-Progress: A Simulation Framework for Domain-Specific System-on-Chips. CoRR abs/1908.03664 (2019) - [i10]Kartikeya Bhardwaj, Radu Marculescu:
Towards Unifying Neural Architecture Space Exploration and Generalization. CoRR abs/1910.00780 (2019) - [i9]Kartikeya Bhardwaj, Naveen Suda, Radu Marculescu:
EdgeAI: A Vision for Deep Learning in IoT Era. CoRR abs/1910.10356 (2019) - 2018
- [j58]Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Machine Learning and Manycore Systems Design: A Serendipitous Symbiosis. Computer 51(7): 66-77 (2018) - [j57]Wonje Choi, Karthi Duraisamy, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems. IEEE Trans. Computers 67(5): 672-686 (2018) - [c128]Chieh Lo, Radu Marculescu:
MetaNN: Accurate Classification of Host Phenotypes From Metagenomic Data Using Neural Networks. BCB 2018: 608-609 - [c127]Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Hybrid on-chip communication architectures for heterogeneous manycore systems. ICCAD 2018: 62 - [c126]Kartikeya Bhardwaj, Radu Marculescu:
Dimensionality Reduction via Community Detection in Small Sample Datasets. PAKDD (3) 2018: 102-114 - [i8]Biresh Kumar Joardar, Ryan Gary Kim, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Learning-based Application-Agnostic 3D NoC Design for Heterogeneous Manycore Systems. CoRR abs/1810.08869 (2018) - [i7]Jiqian Dong, Gopaljee Atulya, Kartikeya Bhardwaj, Radu Marculescu:
A Dynamic Network and Representation LearningApproach for Quantifying Economic Growth fromSatellite Imagery. CoRR abs/1812.00141 (2018) - [i6]Anshul Goyal, Kartikeya Bhardwaj, Radu Marculescu:
Climate Anomalies vs Air Pollution: Carbon Emissions and Anomaly Networks. CoRR abs/1812.02634 (2018) - 2017
- [j56]Chieh Lo, Kartikeya Bhardwaj, Radu Marculescu:
Towards cell-based therapeutics: A bio-inspired autonomous drug delivery system. Nano Commun. Networks 12: 25-33 (2017) - [j55]Chieh Lo, Radu Marculescu:
MPLasso: Inferring microbial association networks using prior microbial knowledge. PLoS Comput. Biol. 13(12) (2017) - [j54]Kartikeya Bhardwaj, Radu Marculescu:
Non-Stationary Bayesian Learning for Global Sustainability. IEEE Trans. Sustain. Comput. 2(3): 304-316 (2017) - [j53]Ryan Gary Kim, Wonje Choi, Zhuo Chen, Janardhan Rao Doppa, Partha Pratim Pande, Diana Marculescu, Radu Marculescu:
Imitation Learning for Dynamic VFI Control in Large-Scale Manycore Systems. IEEE Trans. Very Large Scale Integr. Syst. 25(9): 2458-2471 (2017) - [c125]Chieh Lo, Radu Marculescu:
Inferring Microbial Interactions from Metagenomic Time-series Using Prior Biological Knowledge. BCB 2017: 168-177 - [c124]Kartikeya Bhardwaj, Radu Marculescu:
K-hop learning: a network-based feature extraction for improved river flow prediction. CySWATER@CPSWeek 2017: 15-18 - [c123]Filipe Condessa, Radu Marculescu:
From Ideas to Social Signals: Spatiotemporal Analysis of Social Media Dynamics. SocialSens@CPSWeek 2017: 29-34 - [c122]Ruizhou Ding, Dimitrios Stamoulis, Kartikeya Bhardwaj, Diana Marculescu, Radu Marculescu:
Enhancing precipitation models by capturing multivariate and multiscale climate dynamics. CySWATER@CPSWeek 2017: 39-42 - [c121]Kartikeya Bhardwaj, HingOn Miu, Radu Marculescu:
Discovering Hidden Knowledge in Carbon Emissions Data: A Multilayer Network Approach. DS 2017: 223-238 - [c120]Radu Marculescu:
HiCOMB Keynote. IPDPS Workshops 2017: 252 - [c119]Sohil Shah, Ashwin Raghavachari, Chieh Lo, Radu Marculescu:
Molecular communication with DNA cellular storage system. NANOCOM 2017: 24:1-24:6 - [c118]