Towards heterogeneous solvers for large-scale linear systems. - Stylianos I. Venieris; Grigorios Mingas; Christos-Savvas Bouganis (FPL, 2015)

fpgaConvNet: A Framework for Mapping Convolutional Neural Networks on FPGAs. - Stylianos I. Venieris; Christos-Savvas Bouganis (FCCM, 2016)

fpgaConvNet: Automated Mapping of Convolutional Neural Networks on FPGAs (Abstract Only). - Stylianos I. Venieris; Christos-Savvas Bouganis (FPGA, 2017)

Latency-driven design for FPGA-based convolutional neural networks. - Stylianos I. Venieris; Christos-Savvas Bouganis (FPL, 2017)

fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs. - Stylianos I. Venieris; Christos-Savvas Bouganis (CoRR, 2017)

Approximate FPGA-Based LSTMs Under Computation Time Constraints. - Michalis Rizakis; Stylianos I. Venieris; Alexandros Kouris; Christos-Savvas Bouganis (ARC, 2018)

DroNet: Efficient convolutional neural network detector for real-time UAV applications. - Christos Kyrkou; George Plastiras; Theocharis Theocharides; Stylianos I. Venieris; Christos-Savvas Bouganis (DATE, 2018)

Cascade^CNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks. - Alexandros Kouris; Stylianos I. Venieris; Christos-Savvas Bouganis (FPL, 2018)

f-CNNx: A Toolflow for Mapping Multiple Convolutional Neural Networks on FPGAs. - Stylianos I. Venieris; Christos-Savvas Bouganis (FPL, 2018)

CascadeCNN: Pushing the performance limits of quantisation. - Alexandros Kouris; Stylianos I. Venieris; Christos-Savvas Bouganis (CoRR, 2018)

f-CNNx: A Toolflow for Mapping Multiple Convolutional Neural Networks on FPGAs. - Stylianos I. Venieris; Christos-Savvas Bouganis (CoRR, 2018)

Deploying Deep Neural Networks in the Embedded Space. - Stylianos I. Venieris; Alexandros Kouris; Christos-Savvas Bouganis (CoRR, 2018)

CascadeCNN: Pushing the Performance Limits of Quantisation in Convolutional Neural Networks. - Alexandros Kouris; Stylianos I. Venieris; Christos-Savvas Bouganis (CoRR, 2018)

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions. - Stylianos I. Venieris; Alexandros Kouris; Christos-Savvas Bouganis (ACM Comput. Surv., 2018)

Power-Aware FPGA Mapping of Convolutional Neural Networks. - Alexander Montgomerie-Corcoran; Stylianos I. Venieris; Christos-Savvas Bouganis (FPT, 2019)

Towards Efficient On-Board Deployment of DNNs on Intelligent Autonomous Systems. - Alexandros Kouris; Stylianos I. Venieris; Christos-Savvas Bouganis (ISVLSI, 2019)

MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. - Royson Lee; Stylianos I. Venieris; Lukasz Dudziak; Sourav Bhattacharya; Nicholas D. Lane (MobiCom, 2019)

Poster: MobiSR - Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. - Royson Lee; Stylianos I. Venieris; Lukasz Dudziak; Sourav Bhattacharya; Nicholas D. Lane (MobiCom, 2019)

EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices. - Mário Almeida; Stefanos Laskaridis; Ilias Leontiadis; Stylianos I. Venieris; Nicholas D. Lane (CoRR, 2019)

fpgaConvNet: Mapping Regular and Irregular Convolutional Neural Networks on FPGAs. - Stylianos I. Venieris; Christos-Savvas Bouganis (IEEE Trans. Neural Networks Learn. Syst., 2019)

Automated methodologies for mapping convolutional neural networks on reconfigurable hardware. - Stylianos I. Venieris (2019)

Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions. - Royson Lee; Stylianos I. Venieris; Nicholas D. Lane (DistributedML@CoNEXT, 2020)

A Throughput-Latency Co-Optimised Cascade of Convolutional Neural Network Classifiers. - Alexandros Kouris; Stylianos I. Venieris; Christos-Savvas Bouganis (DATE, 2020)

Journey Towards Tiny Perceptual Super-Resolution. - Royson Lee; Lukasz Dudziak; Mohamed S. Abdelfattah; Stylianos I. Venieris; Hyeji Kim; Hongkai Wen 001; Nicholas D. Lane (ECCV (26), 2020)

Caffe Barista: Brewing Caffe with FPGAs in the Training Loop. - Diederik Adriaan Vink; Aditya Rajagopal; Stylianos I. Venieris; Christos-Savvas Bouganis (FPL, 2020)

HAPI: Hardware-Aware Progressive Inference. - Stefanos Laskaridis; Stylianos I. Venieris; Hyeji Kim; Nicholas D. Lane (ICCAD, 2020)

Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs. - Aditya Rajagopal; Diederik Adriaan Vink; Stylianos I. Venieris; Christos-Savvas Bouganis (ICML, 2020)

SPINN: synergistic progressive inference of neural networks over device and cloud. - Stefanos Laskaridis; Stylianos I. Venieris; Mário Almeida; Ilias Leontiadis; Nicholas D. Lane (MobiCom, 2020)

Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars. - Alexandros Kouris; Stylianos I. Venieris; Michail Rizakis; Christos-Savvas Bouganis (IEEE Consumer Electron. Mag., 2020)

Countering Acoustic Adversarial Attacks in Microphone-equipped Smart Home Devices. - Sourav Bhattacharya; Dionysis Manousakas; Alberto Gil C. P. Ramos; Stylianos I. Venieris; Nicholas D. Lane; Cecilia Mascolo (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020)

How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures. - Stylianos I. Venieris; Ioannis Panopoulos; Ilias Leontiadis; Iakovos S. Venieris (ASAP, 2021)

unzipFPGA: Enhancing FPGA-based CNN Engines with On-the-Fly Weights Generation. - Stylianos I. Venieris; Javier Fernández-Marqués; Nicholas D. Lane (FCCM, 2021)

FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. - Samuel Horváth; Stefanos Laskaridis; Mário Almeida; Ilias Leontiadis; Stylianos I. Venieris; Nicholas D. Lane (NeurIPS, 2021)

OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices. - Stylianos I. Venieris; Ioannis Panopoulos; Iakovos S. Venieris (SMARTCOMP, 2021)

It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. - Ilias Leontiadis; Stefanos Laskaridis; Stylianos I. Venieris; Nicholas D. Lane (HotMobile, 2021)

Multi-Exit Semantic Segmentation Networks. - Alexandros Kouris; Stylianos I. Venieris; Stefanos Laskaridis; Nicholas D. Lane (ECCV (21), 2022)

Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design. - Hongxiang Fan; Thomas Chau 001; Stylianos I. Venieris; Royson Lee; Alexandros Kouris; Wayne Luk; Nicholas D. Lane; Mohamed S. Abdelfattah (MICRO, 2022)

Adaptable mobile vision systems through multi-exit neural networks. - Alexandros Kouris; Stylianos I. Venieris; Stefanos Laskaridis; Nicholas D. Lane (MobiSys, 2022)

Multi-DNN Accelerators for Next-Generation AI Systems. - Stylianos I. Venieris; Christos-Savvas Bouganis; Nicholas D. Lane (CoRR, 2022)

Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs. - Alexandros Kouris; Stylianos I. Venieris; Stefanos Laskaridis; Nicholas D. Lane (CoRR, 2022)

Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions. - Royson Lee; Stylianos I. Venieris; Nicholas D. Lane (ACM Comput. Surv., 2022)

Guest Editorial: Bridging the Gap Between Industry and Academia for Networking Research. - Bo Han 001; Jiasi Chen; Tian Guo 001; Sung-Ju Lee; Viswanathan Swaminathan 001; Stylianos I. Venieris (IEEE Netw., 2022)

DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. - Mário Almeida; Stefanos Laskaridis; Stylianos I. Venieris; Ilias Leontiadis; Nicholas D. Lane (ACM Trans. Embed. Comput. Syst., 2022)

MultiTASC: A Multi-Tenancy-Aware Scheduler for Cascaded DNN Inference at the Consumer Edge. - Sokratis Nikolaidis; Stylianos I. Venieris; Iakovos S. Venieris (ISCC, 2023)

Exploring the Performance and Efficiency of Transformer Models for NLP on Mobile Devices. - Ioannis Panopoulos; Sokratis Nikolaidis; Stylianos I. Venieris; Iakovos S. Venieris (ISCC, 2023)

Sparse-DySta: Sparsity-Aware Dynamic and Static Scheduling for Sparse Multi-DNN Workloads. - Hongxiang Fan; Stylianos I. Venieris; Alexandros Kouris; Nicholas D. Lane (MICRO, 2023)

LifeLearner: Hardware-Aware Meta Continual Learning System for Embedded Computing Platforms. - Young D. Kwon; Jagmohan Chauhan; Hong Jia; Stylianos I. Venieris; Cecilia Mascolo (SenSys, 2023)

TinyTrain: Deep Neural Network Training at the Extreme Edge. - Young D. Kwon; Rui Li 052; Stylianos I. Venieris; Jagmohan Chauhan; Nicholas D. Lane; Cecilia Mascolo (CoRR, 2023)

Multiple-Deep Neural Network Accelerators for Next-Generation Artificial Intelligence Systems. - Stylianos I. Venieris; Christos-Savvas Bouganis; Nicholas D. Lane (Computer, 2023)

Mitigating Memory Wall Effects in CNN Engines with On-the-Fly Weights Generation. - Stylianos I. Venieris; Javier Fernández-Marqués; Nicholas D. Lane (ACM Trans. Design Autom. Electr. Syst., 2023)

TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge. - Young D. Kwon; Rui Li 052; Stylianos I. Venieris; Jagmohan Chauhan; Nicholas Donald Lane; Cecilia Mascolo (ICML, 2024)

Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. - Royson Lee; Rui Li 052; Stylianos I. Venieris; Timothy M. Hospedales; Ferenc Huszár; Nicholas D. Lane (WACV, 2024)

Hardware-Aware Parallel Prompt Decoding for Memory-Efficient Acceleration of LLM Inference. - Hao Mark Chen; Wayne Luk; Ka Fai Cedric Yiu; Rui Li 052; Konstantin Mishchenko; Stylianos I. Venieris; Hongxiang Fan (CoRR, 2024)

MultiTASC++: A Continuously Adaptive Scheduler for Edge-Based Multi-Device Cascade Inference. - Sokratis Nikolaidis; Stylianos I. Venieris; Iakovos S. Venieris (CoRR, 2024)

The Future of Consumer Edge-AI Computing. - Stefanos Laskaridis; Stylianos I. Venieris; Alexandros Kouris; Rui Li 052; Nicholas D. Lane (IEEE Pervasive Comput., 2024)

NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution. - Stylianos I. Venieris; Mário Almeida; Royson Lee; Nicholas D. Lane (IEEE Trans. Mob. Comput., 2024)

CARIn: Constraint-Aware and Responsive Inference on Heterogeneous Devices for Single- and Multi-DNN Workloads. - Ioannis Panopoulos; Stylianos I. Venieris; Iakovos S. Venieris (ACM Trans. Embed. Comput. Syst., 2024)

Progressive Mixed-Precision Decoding for Efficient LLM Inference. - Hao Mark Chen; Fuwen Tan; Alexandros Kouris; Royson Lee; Hongxiang Fan; Stylianos I. Venieris (ICLR, 2025)

FedP2EFT: Federated Learning to Personalize Parameter Efficient Fine-Tuning for Multilingual LLMs. - Royson Lee; Minyoung Kim 001; Fady Rezk; Rui Li 052; Stylianos I. Venieris; Timothy M. Hospedales (CoRR, 2025)

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT. - Ioannis Panopoulos; Maria-Lamprini A. Bartsioka; Sokratis Nikolaidis; Stylianos I. Venieris; Dimitra I. Kaklamani; Iakovos S. Venieris (CoRR, 2025)

HierarchicalPrune: Position-Aware Compression for Large-Scale Diffusion Models. - Young D. Kwon; Rui Li 052; Sijia Li; Da Li 001; Sourav Bhattacharya; Stylianos I. Venieris (CoRR, 2025)