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08/19/2023
Error Probability Bounds for Invariant Causal Prediction via Multiple Access Channels
We consider the problem of lower bounding the error probability under th...
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07/19/2023
Communication-Efficient Distribution-Free Inference Over Networks
Consider a star network where each local node possesses a set of distrib...
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07/15/2023
Identifying Direct Causes using Intervened Target Variable
Identifying the direct causes or causal parents of a target variable is ...
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07/06/2023
Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning
We propose a novel framework for few-shot learning by leveraging large-s...
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06/27/2023
SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Reproducible Scenes
We present a new reproducible benchmark for evaluating robot manipulatio...
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06/14/2023
Pedestrian Recognition with Radar Data-Enhanced Deep Learning Approach Based on Micro-Doppler Signatures
As a hot topic in recent years, the ability of pedestrians identificatio...
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05/10/2023
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences
Learning causal structure among event types from discrete-time event seq...
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02/07/2023
Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction
We introduce a novel robotic system for improving unseen object instance...
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02/01/2023
Deep Dependency Networks for Multi-Label Classification
We propose a simple approach which combines the strengths of probabilist...
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01/14/2023
Generalized Invariant Matching Property via LASSO
Learning under distribution shifts is a challenging task. One principled...
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12/21/2022
SLGTformer: An Attention-Based Approach to Sign Language Recognition
Sign language is the preferred method of communication of deaf or mute p...
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11/29/2022
On Large-Scale Multiple Testing Over Networks: An Asymptotic Approach
This work concerns developing communication- and computation-efficient m...
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11/21/2022
Mean Shift Mask Transformer for Unseen Object Instance Segmentation
Segmenting unseen objects is a critical task in many different domains. ...
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10/05/2022
Sample-and-Forward: Communication-Efficient Control of the False Discovery Rate in Networks
This work concerns controlling the false discovery rate (FDR) in network...
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08/22/2022
Learning Invariant Representations under General Interventions on the Response
It has become increasingly common nowadays to collect observations of fe...
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07/30/2022
Few-shot Single-view 3D Reconstruction with Memory Prior Contrastive Network
3D reconstruction of novel categories based on few-shot learning is appe...
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07/06/2022
NeuralGrasps: Learning Implicit Representations for Grasps of Multiple Robotic Hands
We introduce a neural implicit representation for grasps of objects from...
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07/06/2022
FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments
We introduce the Few-Shot Object Learning (FewSOL) dataset for object re...
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06/29/2022
Lower Bounds on the Error Probability for Invariant Causal Prediction
It is common practice to collect observations of feature and response pa...
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06/23/2022
A Manifold-based Airfoil Geometric-feature Extraction and Discrepant Data Fusion Learning Method
Geometrical shape of airfoils, together with the corresponding flight co...
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05/19/2022
HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handovers
We introduce a new simulation benchmark "HandoverSim" for human-to-robot...
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05/18/2022
An Invariant Matching Property for Distribution Generalization under Intervened Response
The task of distribution generalization concerns making reliable predict...
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03/23/2022
A Multi-Characteristic Learning Method with Micro-Doppler Signatures for Pedestrian Identification
The identification of pedestrians using radar micro-Doppler signatures h...
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03/06/2022
Variable Selection with the Knockoffs: Composite Null Hypotheses
The Fixed-X knockoff filter is a flexible framework for variable selecti...
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01/31/2022
Communication-Efficient Distributed Multiple Testing for Large-Scale Inference
The Benjamini-Hochberg (BH) procedure is a celebrated method for multipl...
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12/31/2021
iCaps: Iterative Category-level Object Pose and Shape Estimation
This paper proposes a category-level 6D object pose and shape estimation...
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11/30/2021
TALISMAN: Targeted Active Learning for Object Detection with Rare Classes and Slices using Submodular Mutual Information
Deep neural networks based object detectors have shown great success in ...
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09/12/2021
Differentially Private Variable Selection via the Knockoff Filter
The knockoff filter, recently developed by Barber and Candes, is an effe...
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08/31/2021
A Subsampling-Based Method for Causal Discovery on Discrete Data
Inferring causal directions on discrete and categorical data is an impor...
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07/04/2021
Hierarchical Policies for Cluttered-Scene Grasping with Latent Plans
6D grasping in cluttered scenes is a longstanding robotic manipulation p...
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06/29/2021
RICE: Refining Instance Masks in Cluttered Environments with Graph Neural Networks
Segmenting unseen object instances in cluttered environments is an impor...
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04/09/2021
DexYCB: A Benchmark for Capturing Hand Grasping of Objects
We introduce DexYCB, a new dataset for capturing hand grasping of object...
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04/01/2021
RGB-D Local Implicit Function for Depth Completion of Transparent Objects
Majority of the perception methods in robotics require depth information...
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02/19/2021
Learning Composable Behavior Embeddings for Long-horizon Visual Navigation
Learning high-level navigation behaviors has important implications: it ...
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12/23/2020
Causal Inference Using Linear Time-Varying Filters with Additive Noise
Causal inference using the restricted structural causal model framework ...
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10/15/2020
Aerodynamic Data Predictions Based on Multi-task Learning
The quality of datasets is one of the key factors that affect the accura...
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10/02/2020
Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds
6D robotic grasping beyond top-down bin-picking scenarios is a challengi...
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09/13/2020
Information Laundering for Model Privacy
In this work, we propose information laundering, a novel framework for e...
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07/30/2020
Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation
Segmenting unseen objects in cluttered scenes is an important skill that...
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07/16/2020
Unseen Object Instance Segmentation for Robotic Environments
In order to function in unstructured environments, robots need the abili...
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12/01/2019
LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation
Current 6D object pose estimation methods usually require a 3D model for...
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11/22/2019
Manipulation Trajectory Optimization with Online Grasp Synthesis and Selection
In robot manipulation, planning the motion of a robot manipulator to gra...
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09/26/2019
Scaling Local Control to Large-Scale Topological Navigation
Visual topological navigation has been revitalized recently thanks to th...
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09/23/2019
Self-supervised 6D Object Pose Estimation for Robot Manipulation
To teach robots skills, it is crucial to obtain data with supervision. S...
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07/30/2019
The Best of Both Modes: Separately Leveraging RGB and Depth for Unseen Object Instance Segmentation
In order to function in unstructured environments, robots need the abili...
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05/22/2019
PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking
Tracking 6D poses of objects from videos provides rich information to a ...
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04/03/2019
Neural Autonomous Navigation with Riemannian Motion Policy
End-to-end learning for autonomous navigation has received substantial a...
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12/06/2018
Object Discovery in Videos as Foreground Motion Clustering
We consider the problem of providing dense segmentation masks for object...
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09/27/2018
Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects
Using synthetic data for training deep neural networks for robotic manip...
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06/30/2018
