Learning without feedback: Direct random target projection as a feedback-alignment algorithm with layerwise feedforward training. - Charlotte Frenkel; Martin Lefebvre 002; David Bol (CoRR, 2019)

A 0.086-mm2 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS. - Charlotte Frenkel; Martin Lefebvre 002; Jean-Didier Legat; David Bol (IEEE Trans. Biomed. Circuits Syst., 2019)

A 0.2-to-3.6TOPS/W Programmable Convolutional Imager SoC with In-Sensor Current-Domain Ternary-Weighted MAC Operations for Feature Extraction and Region-of-Interest Detection. - Martin Lefebvre 002; Ludovic Moreau; Rémi Dekimpe; David Bol (ISSCC, 2021)

SleepRider: a 5.5μW/MHz Cortex-M4 MCU in 28nm FD-SOI with ULP SRAM, Biomedical AFE and Fully-Integrated Power, Clock and Back-Bias Management. - Rémi Dekimpe; Maxime Schramme; Martin Lefebvre 002; Adrian Kneip; Roghayeh Saeidi; Mathieu Xhonneux; Ludovic Moreau; Marco Gonzalez; Thibault Pirson; David Bol (VLSI Circuits, 2021)

A 1-to-4b 16.8-POPS/W 473-TOPS/mm2 6T-based In-Memory Computing SRAM in 22nm FD-SOI with Multi-Bit Analog Batch-Normalization. - Adrian Kneip; Martin Lefebvre 002; Julien Verecken; David Bol (ESSCIRC, 2022)

A 0.9-nA Temperature-Independent 565-ppm/°C Self-Biased Current Reference in 22-nm FDSOI. - Martin Lefebvre 002; Denis Flandre; David Bol (ESSCIRC, 2022)

A Family of Current References Based on 2T Voltage References: Demonstration in 0.18-μm With 0.1-nA PTAT and 1.1-μA CWT 38-ppm/°C Designs. - Martin Lefebvre 002; David Bol (IEEE Trans. Circuits Syst. I Regul. Pap., 2022)

A 1.1- / 0.9-nA Temperature-Independent 213- / 565-ppm/$^ circ$C Self-Biased CMOS-Only Current Reference in 65-nm Bulk and 22-nm FDSOI. - Martin Lefebvre 002; Denis Flandre; David Bol (CoRR, 2023)

A 1.1-/0.9-nA Temperature-Independent 213-/565-ppm/°C Self-Biased CMOS-Only Current Reference in 65-nm Bulk and 22-nm FDSOI. - Martin Lefebvre 002; Denis Flandre; David Bol (IEEE J. Solid State Circuits, 2023)

IMPACT: A 1-to-4b 813-TOPS/W 22-nm FD-SOI Compute-in-Memory CNN Accelerator Featuring a 4.2-POPS/W 146-TOPS/mm2 CIM-SRAM With Multi-Bit Analog Batch-Normalization. - Adrian Kneip; Martin Lefebvre 002; Julien Verecken; David Bol (IEEE J. Solid State Circuits, 2023)

A Mixed-Signal Near-Sensor Convolutional Imager SoC with Charge-Based 4b-Weighted 5-to-84-TOPS/W MAC Operations for Feature Extraction and Region-of-Interest Detection. - Martin Lefebvre 002; David Bol (CICC, 2024)

A 2.5-nA Area-Efficient Temperature-Independent 176-/82-ppm/°C CMOS-Only Current Reference in 0.11-μm Bulk and 22-nm FD-SOI. - Martin Lefebvre 002; David Bol (CoRR, 2024)

A nA-Range Area-Efficient Sub-100-ppm/°C Peaking Current Reference Using Forward Body Biasing in 0.11-μm Bulk and 22-nm FD-SOI. - Martin Lefebvre 002; David Bol (CoRR, 2024)

IMAGINE: An 8-to-1b 22nm FD-SOI Compute-In-Memory CNN Accelerator With an End-to-End Analog Charge-Based 0.15-8POPS/W Macro Featuring Distribution-Aware Data Reshaping. - Adrian Kneip; Martin Lefebvre 002; Pol Maistriaux; David Bol (CoRR, 2024)

A 2.5-nA Area-Efficient Temperature-Independent 176-/82-ppm/°C CMOS-Only Current Reference in 0.11- μ m Bulk and 22-nm FD-SOI. - Martin Lefebvre 002; David Bol (IEEE J. Solid State Circuits, 2024)

A nA-Range Area-Efficient Sub-100-ppm/°C Peaking Current Reference Using Forward Body Biasing in 0.11- μ m Bulk and 22-nm FD-SOI. - Martin Lefebvre 002; David Bol (IEEE J. Solid State Circuits, 2025)

MANTIS: A Mixed-Signal Near-Sensor Convolutional Imager SoC Using Charge-Domain 4b-Weighted 5-to-84-TOPS/W MAC Operations for Feature Extraction and Region-of-Interest Detection. - Martin Lefebvre 002; David Bol (IEEE J. Solid State Circuits, 2025)