These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution (as opposed to the distance between two points), making it the multivariate equivalent of the Euclidean distance.
It is often used in multivariate anomaly detection, classification on highly imbalanced datasets and one-class classification.
Related use cases :
Learning a Mahalanobis distance metric for data clustering and classification
Uploaded on Oct 24, 2022Distance metric is a key issue in many machine learning algorithms. This paper considers a general problem of learning from pairwise constraints in the form of must-links and c...
Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving
Uploaded on Apr 2, 2024Multimodal Large Language Models (MLLMs) have experienced significant
advancements recently. Nevertheless, challenges persist in the accurate
recognition and comprehension of intri...
CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning
Uploaded on Apr 2, 2024In Multiple Object Tracking (MOT), tracking-by-detection methods have stood
the test for a long time, which split the process into two parts according to
the definition: object det...
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations
Uploaded on Apr 2, 2024Object detectors often perform poorly on data that differs from their
training set. Domain adaptive object detection (DAOD) methods have recently
demonstrated strong results on add...
PUAD: Frustratingly Simple Method for Robust Anomaly Detection
Uploaded on Apr 2, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
PaddingFlow: Improving Normalizing Flows with Padding-Dimensional Noise
Uploaded on Apr 2, 2024Multimodal Large Language Models (MLLMs) excel in generating responses based
on visual inputs. However, they often suffer from a bias towards generating
responses similar to their ...
Self-supervised Video Object Segmentation with Distillation Learning of Deformable Attention
Uploaded on Apr 2, 2024We present DeepSeek-VL, an open-source Vision-Language (VL) Model designed
for real-world vision and language understanding applications. Our approach is
structured around three ke...
The VampPrior Mixture Model
Uploaded on Apr 2, 2024Language models (LMs) have proven to be powerful tools for psycholinguistic
research, but most prior work has focused on purely behavioural measures (e.g.,
surprisal comparisons). ...
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Uploaded on Apr 22, 2024In this work, we introduce Mini-Gemini, a simple and effective framework
enhancing multi-modality Vision Language Models (VLMs). Despite the
advancements in VLMs facilitating basic...
Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval
Uploaded on Apr 22, 2024Vision Transformer (ViT) self-attention mechanism is characterized by feature
collapse in deeper layers, resulting in the vanishing of low-level visual
features. However, such feat...
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
Uploaded on Apr 22, 2024Multimodal Large Language Models (MLLMs) have experienced significant
advancements recently. Nevertheless, challenges persist in the accurate
recognition and comprehension of intri...
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Uploaded on Apr 22, 2024We propose a novel model-selection method for dynamic real-life networks. Our
approach involves training a classifier on a large body of synthetic network
data. The data is generat...
ProMISe: Promptable Medical Image Segmentation using SAM
Uploaded on Apr 22, 2024This paper introduces fourteen novel datasets for the evaluation of Large
Language Models' safety in the context of enterprise tasks. A method was
devised to evaluate a model's saf...
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
Uploaded on Apr 22, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Uploaded on May 21, 2024In this work, we introduce Mini-Gemini, a simple and effective framework
enhancing multi-modality Vision Language Models (VLMs). Despite the
advancements in VLMs facilitating basic...
Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval
Uploaded on May 21, 2024Vision Transformer (ViT) self-attention mechanism is characterized by feature
collapse in deeper layers, resulting in the vanishing of low-level visual
features. However, such feat...
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
Uploaded on May 21, 2024Multimodal Large Language Models (MLLMs) have experienced significant
advancements recently. Nevertheless, challenges persist in the accurate
recognition and comprehension of intri...
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Uploaded on May 21, 2024We propose a novel model-selection method for dynamic real-life networks. Our
approach involves training a classifier on a large body of synthetic network
data. The data is generat...
ProMISe: Promptable Medical Image Segmentation using SAM
Uploaded on May 21, 2024This paper introduces fourteen novel datasets for the evaluation of Large
Language Models' safety in the context of enterprise tasks. A method was
devised to evaluate a model's saf...
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
Uploaded on May 21, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
Uploaded on Jun 5, 2024In this work, we introduce Mini-Gemini, a simple and effective framework
enhancing multi-modality Vision Language Models (VLMs). Despite the
advancements in VLMs facilitating basic...
Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval
Uploaded on Jun 5, 2024Vision Transformer (ViT) self-attention mechanism is characterized by feature
collapse in deeper layers, resulting in the vanishing of low-level visual
features. However, such feat...
HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images
Uploaded on Jun 5, 2024Multimodal Large Language Models (MLLMs) have experienced significant
advancements recently. Nevertheless, challenges persist in the accurate
recognition and comprehension of intri...
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Uploaded on Jun 5, 2024We propose a novel model-selection method for dynamic real-life networks. Our
approach involves training a classifier on a large body of synthetic network
data. The data is generat...
ProMISe: Promptable Medical Image Segmentation using SAM
Uploaded on Jun 5, 2024This paper introduces fourteen novel datasets for the evaluation of Large
Language Models' safety in the context of enterprise tasks. A method was
devised to evaluate a model's saf...
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
Uploaded on Jun 5, 2024The BigCode project, an open-scientific collaboration focused on the
responsible development of Large Language Models for Code (Code LLMs),
introduces StarCoder2. In partnership wi...
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