tweetindex
DE

Jure Leskovec ✓

@jure · Stanford, CA · joined 12 Aug 2007

Professor of #computerscience @Stanford; Co-founder at https://t.co/hhm1j5wP0f #machinelearning #graphs.

45 059Followers
428Following
1 522Posts total
77.8KViews on collected posts

Neueste Beiträge

Excited to see this out! Relational learning needs strong benchmarks, standardized evaluation, and easy ways to bring methods to real-world relational data. 4.2K views · 24 likes · 2 reposts · 1 replies Open on X →
We’re happy to announce our first release in relational learning at Prior Labs, continuing our commitment to open science. We open-source three pieces of software that we expect to accelerate research in the field towards meaningful, real-world impact. First and foremost, we ht 8.6K views · 45 likes · 11 reposts · 0 replies Open on X →
Fun conversation with @ItaiYanai on @nightsciencepod about what happens when AI starts doing science: agents that find patterns, generate hypotheses, and try to falsify them with more data. We also got into taste, judgment, and where human scientists still matter most. 13.8K views · 80 likes · 10 reposts · 2 replies Open on X →
How would you let the LLM dream? [...] In a sense, to replay things, organize them, think about them so that tomorrow when we wake up, our thoughts are more organized than just input-output-input-output. –Jure Leskovec, Stanford Professor, @jure https://t.co/CzSbIgX4QY 17.4K views · 24 likes · 4 reposts · 3 replies Open on X →
Exciting milestone for @KexinHuang5 and the @phylo_bio team. Putting AI scientist systems directly in the hands of discovery scientists is where the next big gains in biomedical AI will come from. 6K views · 33 likes · 4 reposts · 5 replies Open on X →
@jure @Nature It took 3 years??? How I didnt even know it was still a preprint 250 views · 1 likes · 0 reposts · 1 replies Open on X →
Paper: https://t.co/IcYq4PVYC9 Code: https://t.co/xFKZaQol5X Thanks so much to the team @YanayRosen @yusufroohani @StephenQuake! 1.2K views · 2 likes · 0 reposts · 0 replies Open on X →
Excited to share that our Universal Cell Embedding (UCE) paper is published in @Nature ! Single-cell RNA sequencing data gives us an unprecedented look into the diversity of cell biology, but analysis has often been limited to the specific dataset or atlas that was collected. 18.1K views · 246 likes · 45 reposts · 5 replies Open on X →
We designed and trained the UCE foundation model so that any new data, from any disease, tissue or species, could be mapped into the same universal representation space, without fine tuning or retraining. 1.9K views · 6 likes · 0 reposts · 1 replies Open on X →
UCE connects molecular and cellular scales of biology. Genes are more than just columns in an expression matrix: in UCE, they are encoded according to the proteins they produce, using ESM, embedding novel species not seen during training, across 100Ms of years of evolution. 1.9K views · 5 likes · 0 reposts · 1 replies Open on X →
Modern multimodal models aren't a single decode loop anymore; they're composite. M* is one runtime that serves them all, and it matches or beats every specialized system: up to 2.7× on omni TTS, 12.5× on world-model rollouts. Learn more here: https://t.co/3MwvdJiJaQ https://t.co/ 4.3K views · 28 likes · 6 reposts · 1 replies Open on X →

Im Vergleich zu Konten gleicher Größe

11 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 10K–100K Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.

Medianaufrufe4 314dieses Konto924Median für 10K–100K
Reichweite, %9.57%dieses Konto3.62%Median für 10K–100K
Interaktion, %0.67%dieses Konto1.52%Median für 10K–100K
KennzahlDieses KontoMedian für 10K–100KVerhältnis
Medianaufrufe pro Beitrag4 3149244.67×
Reichweite (Aufrufe ÷ Follower)9.57%3.62%2.64×
Interaktionsrate0.67%1.52%0.44×

Weitere Konten dieser Größe →   Mit einem anderen Konto vergleichen →   Wie diese Vergleichswerte entstehen →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

4.3K6 Jul
1.9K13 Jul
1.9K
18.1K
1.2K
250
6K28 Jul
17.4K11 Aug
13.8K13 Aug
8.6K18 Aug
4.2K19 Aug

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.81%6 Jul
0.31%13 Jul
0.42%
1.64%
0.16%
0.80%
0.70%28 Jul
0.19%11 Aug
0.67%13 Aug
0.70%18 Aug
0.64%19 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes58.8%494 in total
Reposts9.8%82 in total
Replies2.4%20 in total
Quotes1.2%10 in total
Bookmarks27.9%234 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Ähnliche Konten