4 citations · 5 across the 12 of their papers we have counts for
13 papers
Geo-vision: Native-Resolution Geometry and Sampled Topology for Vehicle-Part Damage Classification
Usef Faghihi, Amir Saki, Serge Jonathan Kogbeti-Wongo
Geo-vision classifies vehicle-part damage using a fixed representation combining appearance, multiscale geometry, orientation, and sampled digital topology. Connected components, h…
Common-Witness Certificates and Sharp Feature Bounds for Counterfactual Image Auditing
Usef Faghihi, Amir Saki
An image editor may satisfy every regional plausibility constraint separately even when no single latent explanation fits the complete output. We formalize this local-to-global fai…
Causal inference for group-contaminated structured outcomes: observable quotients, lossless reduction and exact randomization inference
Usef Faghihi, Amir Saki
Structured potential outcomes such as microscopy images may be recorded after an unknown, unit-specific transformation. If that transformation can depend on treatment, covariates o…
Global and Local Topology-Aware Attention with Persistent Homology and Euler Biases for Time-Series Forecasting
Usef Faghihi, Amir Saki
Scientific time series often encode predictive geometric structure, including connectivity, cycles, shell-like geometry, directional changes, and nonlinear neighborhoods, that stan…
Beyond Means: Topological Causal Effects under Persistent-Homology Ignorability
Amir Saki, Usef Faghihi
Average treatment effects (ATE) and conditional average treatment effects (CATE) are foundational causal estimands, but they target changes in expected outcomes and can miss treatm…
Causal Deep Q Network
Elouanes Khelifi, Amir Saki, Usef Faghihi
Deep Q Networks (DQN) have shown remarkable success in various reinforcement learning tasks. However, their reliance on associative learning often leads to the acquisition of spuri…
Integrating Fuzzy Logic with Causal Inference: Enhancing the Pearl and Neyman-Rubin Methodologies
Amir Saki, Usef Faghihi
In this paper, we generalize the Pearl and Neyman-Rubin methodologies in causal inference by introducing a generalized approach that incorporates fuzzy logic. Indeed, we introduce…
Probabilistic Easy Variational Causal Effect
Usef Faghihi, Amir Saki
Let and be random vectors, and . In this paper, on the one hand, for the case that and are continuous, by using the ideas from the total variation and the…
Probabilistic Variational Causal Approach in Observational Studies
Usef Faghihi, Amir Saki
In this paper, we introduce a new causal methodology that accounts for the rarity and frequency of events in observational studies based on their relevance to the underlying proble…
A Fundamental Probabilistic Fuzzy Logic Framework Suitable for Causal Reasoning
Amir Saki, Usef Faghihi
In this paper, we introduce a fundamental framework to create a bridge between Probability Theory and Fuzzy Logic. Indeed, our theory formulates a random experiment of selecting cr…
On the geometric and Riemannian structure of the spaces of group equivariant non-expansive operators
Pasquale Cascarano, Patrizio Frosini, Nicola Quercioli +1
Group equivariant non-expansive operators have been recently proposed as basic components in topological data analysis and deep learning. In this paper we study some geometric prop…
Complemented lattices of subracks
A. Saki, D. Kiani
In this paper, a question due to Heckenberger, Shareshian and Welker on racks in [7] is positively answered. A rack is a set together with a selfdistributive bijective binary opera…
The Lattice of subracks is atomic
Amir Saki, Dariush Kiani
A rack is a set together with a self-distributive bijective binary operation. In this paper, we give a positive answer to a question due to Heckenberger, Shareshian and Welker. Ind…