Search Results for author: Hikaru Shindo

Found 9 papers, 7 papers with code

DeiSAM: Segment Anything with Deictic Prompting

1 code implementation21 Feb 2024 Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Singh Dhami, Patrick Schramowski, Kristian Kersting

To remedy this issue, we propose DeiSAM -- a combination of large pre-trained neural networks with differentiable logic reasoners -- for deictic promptable segmentation.

Image Segmentation Segmentation +1

Learning Differentiable Logic Programs for Abstract Visual Reasoning

1 code implementation3 Jul 2023 Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting

However, due to the memory intensity, most existing approaches do not bring the best of the expressivity of first-order logic, excluding a crucial ability to solve abstract visual reasoning, where agents need to perform reasoning by using analogies on abstract concepts in different scenarios.

Program induction Visual Reasoning

V-LoL: A Diagnostic Dataset for Visual Logical Learning

1 code implementation13 Jun 2023 Lukas Helff, Wolfgang Stammer, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

Despite the successes of recent developments in visual AI, different shortcomings still exist; from missing exact logical reasoning, to abstract generalization abilities, to understanding complex and noisy scenes.

Logical Reasoning Visual Reasoning

Neural Meta-Symbolic Reasoning and Learning

no code implementations21 Nov 2022 Zihan Ye, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

To make deep learning do more from less, we propose the first neural meta-symbolic system (NEMESYS) for reasoning and learning: meta programming using differentiable forward-chaining reasoning in first-order logic.

Neuro-Symbolic Forward Reasoning

1 code implementation18 Oct 2021 Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting

NSFR factorizes the raw inputs into the object-centric representations, converts them into probabilistic ground atoms, and finally performs differentiable forward-chaining inference using weighted rules for inference.


Differentiable Inductive Logic Programming for Structured Examples

1 code implementation2 Mar 2021 Hikaru Shindo, Masaaki Nishino, Akihiro Yamamoto

Our framework can be scaled to deal with complex programs that consist of several clauses with function symbols.

Inductive logic programming

Metric Learning for Ordered Labeled Trees with pq-grams

1 code implementation9 Mar 2020 Hikaru Shindo, Masaaki Nishino, Yasuaki Kobayashi, Akihiro Yamamoto

In order to perform metric learning based on pq-grams, we propose a new differentiable parameterized distance, weighted pq-gram distance.

General Classification Metric Learning

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