Khurshed P. Fitter @_glazedonuts_
MSc. Quantum Science @EPFL_en working on quantum information and algorithms. sites.google.com/view/kpfitter Lausanne, Switzerland Joined October 2017-
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I am looking for a talented postdoc to join my group @EPFL @cqs_lab. Goal is to develop and apply state-of-the-art neural quantum states for electronic structure and related applications. Position to be filled soon, excellent conditions! Apply: epfl.ch/labs/cqsl/job-…
we need a 3 day weekend: 1 for errands 1 for social activities 1 for staying in bed like we’ve got some victorian wasting disease
An astonishing fact.
I am excited to share my new work with @hippoquantus & Cécilia Lancien about measurement incompatibility in random POVMs scirate.com/arxiv/2507.206… TLDR: random measurements are almost maximally incompatible 🤯 A thread 🧵⬇️
theregister.com/2025/07/17/qua… Some objectivity and common sense are refreshing, among the recurring pseudo news of “impending doom” that quantum computing would bring to public-key cryptosystems
We have an opening @EPFL_en for a Condensed Matter/ Interacting Quantum Matter **theorist**, at our Physics Institute. Appointment is at the level of the tenure track assistant professor, with generous support and excellent conditions. DM for more info. epfl.ch/about/working/…
🎉 Our paper “𝐻𝑜𝑤 𝑡𝑜 𝑇𝑟𝑎𝑖𝑛 𝑌𝑜𝑢𝑟 𝐿𝐿𝑀 𝑊𝑒𝑏 𝐴𝑔𝑒𝑛𝑡: 𝐴 𝑆𝑡𝑎𝑡𝑖𝑠𝑡𝑖𝑐𝑎𝑙 𝐷𝑖𝑎𝑔𝑛𝑜𝑠𝑖𝑠” got an 𝐨𝐫𝐚𝐥 at next week’s 𝗜𝗖𝗠𝗟 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗼𝗻 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗨𝘀𝗲 𝗔𝗴𝗲𝗻𝘁𝘀! 🖥️🧠 We present the 𝐟𝐢𝐫𝐬𝐭 𝐥𝐚𝐫𝐠𝐞-𝐬𝐜𝐚𝐥𝐞…
New paper with my PhD student Miao Hu on entanglement scaling in Random Tensor Networks arxiv.org/abs/2506.23894
🚀 Paper: arxiv.org/abs/2503.19377 🚀 Code: github.com/Trustworthy-ML… 🚀 Project site: lilywenglab.github.io/posthoc-genera… Thanks to my co-authors, Ge Yan, @sun_chung_en, @tuomasoi, and my PhD advisor @LilyWeng_
📈 Our methods deliver: ✅ Up to +31% stronger steerability vs prior SOTA ✅ 4–15× faster training ✅ Compatible with both GANs and diffusion models
💡 Key contributions: CB-AE: First method for post-hoc interpretable generative models. → Works with frozen pretrained models – no real concept-labeled images needed. CC: Optimization-based concept intervention → Strong steerability + high-quality outputs
🔍 We introduce two novel methods, Concept Bottleneck Autoencoder (CB-AE) and Concept Controller (CC) that bring interpretability and concept-level controllable generation to deep generative models – with minimal concept supervision.
⚡Interested in making pretrained generative models interpretable with minimal training and annotations? I'll be presenting our paper, Interpretable Generative Models through Post-hoc Concept Bottlenecks, at #CVPR2025 today in Poster Session 2 (4 pm - 6 pm CDT) at poster #266!
A 🧵 on our recent work at #ICRA25. PIP-Loco: A Proprioceptive Infinite Horizon Planning Framework for Quadrupedal Robot Locomotion (stochlab.com/PIP-Loco)
Interpreting Neurons in Deep Vision Networks with Language Models Nicholas Bai, Rahul Ajay Iyer, Tuomas Oikarinen, Akshay R. Kulkarni, Tsui-Wei Weng. Action editor: Antoine Ledent. openreview.net/forum?id=x1dXv… #neuron #neurons #deep
Really hope this is done everywhere. This would require homeowners to maintain a soil surface in the designated setback areas, allowing rainwater to percolate naturally.
Twitter Tech Bros: No one can worship Elon like us Random Bengaluru MRAs: Hold our agarbattis
Just gonna re-up this thread from two years ago now that GPT-4.5 has shipped and it's basically too big to serve.
Just gonna re-up this thread from two years ago now that GPT-4.5 has shipped and it's basically too big to serve.
Looking for a talented postdoc to join my group @cqs_lab @EPFL_en! 🇨🇭 Research Topics Include: Neural Quantum States, Many-Body Systems, Ab-Initio & Quantum Chemistry...etc Start: Fall 2025, excellent conditions Apply: epfl.ch/labs/cqsl/job-…
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