Maxim Bonnaerens
Maxim Bonnaerens
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Gaussian Splatting
DUSt3R
Mip-NeRF 360
Mip-NeRF
Token Merging: Your ViT But Faster
Anchor Pruning for Object Detection
Accurate, Large Minibatch SGD
Attention Is All You Need
Barlow Twins
Batch Normalization
Deep Reinforcement Learning
DETR
Dice Loss
Diffusion Models
Dilated Convolutions
Distilling the Knowledge in a Neural Network
Instant-NGP
Latent Diffusion Models
Learned Thresholds Token Merging and Pruning for Vision Transformers
LoRA
Mixture-of-Experts with Expert Choice Routing
MobileNetV1
MobileNetV2
NeRF
Once-for-All
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Proximal Policy Optimization Algorithms
RetinaNet
Segment Anything
SETR
SimCLR
Squeeze-and-Excitation Networks
SSD: Single Shot MultiBox Detector
Stable Diffusion
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
The Lottery Ticket Hypothesis
Variational Auto-Encoder
Vision Transformers
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Automatic
Point Cloud Processing
CREAtIve: Reconfigurable Embedded Artificial Intelligence
cREAtIve targets the development of novel highly-adaptable embedded deep learning solutions for automotive and traffic monitoring …
Poona Bahrebar
,
Leon Denis
,
Maxim Bonnaerens
,
Kristof Coddens
,
Joni Dambre
,
Wouter Favoreel
,
Illia Khvastunov
,
Adrian Munteanu
,
Hung Nguyen-Duc
,
Stefan Schulte
,
Dirk Stroobandt
,
Ramses Valvekens
,
Nick Van Den Broeck
,
Geert Verbruggen
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